CDS-bench: Task definitions
84 tasks total: 65 individual task types and 19 composition tasks.
Proposal for evaluating procedural reasoning and constrained design on coding DNA sequences. This document specifies task types, easy and hard prompt templates, scoring rules, and composition tasks.
Six examples from the 84 tasks
Four individual tasks and two composition tasks. Each starts from supplied coding DNA and leads to one required answer. For RNA and protein tasks, input preparation is labeled separately. Task titles link to the full definitions.
1 · Individual task
Translate DNA to protein
ATG GCT TAAATGMGCTATAASTOPMA
The first in-frame stop ends translation and is omitted from the answer.
2 · Individual task
Disrupt a specified local hairpin
ATG GGA AAA TCC TAAExpose/edit bases 10–11 only; preserve MGKS.
ATGGGAAAAAGCTAA
Two targeted stem contacts break; protein MGKS remains unchanged.
3 · Individual task
Digest with trypsin rules
ATG GCT AAA CGT CCT GCT AAA TAAInput preparation: translate to MAKRPAK.
K3 │ cut · R4–P5 stays intact
[
{"start":1,"end":3,"peptide":"MAK"},
{"start":4,"end":7,"peptide":"RPAK"}
]Return both fragments in protein order, with inclusive residue coordinates.
4 · Individual task
Remove specified DNA motifs
ATG GAA TTC TGARemove GAATTC; preserve protein MEF and fixed terminal codons.
TTC TTTF FATG GAA TTT TGAGAATTC absent · MEF unchanged
ATGGAATTTTGA
Choose the first valid DNA string in A<C<G<T order; a valid rewrite alone is insufficient.
5 · Composition task
From CDS panel to a diagnostic peptide
ATG GCT AAA GCT GGT AAA TAAATG GCT AAA GGT GCT AAA TAA
MAKAGKMAKGAK
MAK │ AGKMAK │ GAK
AGK
MAK is shared. AGK occurs only in the target digest; select by length, then alphabetical order.
6 · Composition task
From specified RNA edits to protein
ATG CAA GGT TAAAUG CAA GGU UAAAUG UAA GGU UAAM
The new UAA stops translation before GGU. The unedited CDS would encode MQG.
Biological scope and supplied inputs
The starting sequence is a complete, spliced CDS with its coding strand and translation start supplied. Tasks do not require gene discovery, splice-site identification, or recognition of a protein family from learned sequence patterns.
What an instance can supply
- A CDS, or a clearly identified panel of CDSs.
- A requested edit, motif, guide, pairing map, or coding module.
- Custom score tables, allowed edits, and numerical bounds.
What the benchmark does not ask for
- Gene discovery, arbitrary genomic splicing, or isoform prediction.
- Unannotated biological function, folding, expression, or guide efficacy.
- Noncoding-RNA maturation or whole-transcript processing.
RNA and protein inputs are obtained by transcribing or translating the supplied CDS. Composition tasks explicitly combine the named operations and specify the final answer.
Shared sequence conventions
5′→3′ coding DNA; bases may be separated by spaces. All coordinates are 1-based inclusive unless a field explicitly says otherwise. Ordinary translation uses NCBI code 11. First in-frame stop terminates; no stop character appears in the protein.
Synonymous rewrites keep length, first codon, terminal stop, and translated protein fixed. Alternative codes can be separate future rule sets; v0.3 does not silently substitute one.
Easy and hard variants
Each instance has an easy prompt and a hard prompt. They differ only in the biological reference information supplied. The sequence, edits, constraints, correct answer, and scoring rules are the same in both. When the task rules already supply everything needed, the two prompts are identical.
Example: Calculate mean hydropathy (protein.mean_hydropathy). Both variants ask for the average hydropathy of the protein encoded by the same CDS. These illustrative excerpts abbreviate the reference tables and omit the shared answer-format instructions.
Reference supplied
The prompt supplies translation rules, all 64 codon assignments, and all 20 amino-acid hydropathy scores.
REFERENCE
Read the CDS in groups of three bases from base 1. The annotated initiator gives M. End at the first in-frame stop; omit it from the protein.
NCBI code 11 codons:
ATG=M, GCT=A, TAA=STOP, … [64 entries]
Kyte–Doolittle residue scores:
A=1.8, M=1.9, V=4.2, … [20 entries]
TASK
Translate the CDS and average the scores of its amino acids. Return one number with 4 decimal places.
cds: {{cds}}Reference knowledge assumed
The model must know the codon assignments, initiator and stop rules, and numerical residue scores implied by the two reference names.
Translate this CDS using NCBI genetic code 11. Return its whole-protein mean Kyte–Doolittle hydropathy as one number with 4 decimal places.
cds: {{cds}}A custom pairing-score table, edit budget, allowed mutation set, or host-specific codon weights must remain supplied in both variants. Those are instance data. Hard prompts should never require guessing an unpublished convention.
A hard prompt can name an established biological reference and expect the model to supply the underlying facts. For example, “use the Kyte–Doolittle scale” requires knowing the hydropathy score for each amino acid. “Translate using NCBI genetic code 11” requires knowing the codon-to-amino-acid assignments, stop codons, and how annotated initiator codons are translated. Easy prompts provide these tables and rules explicitly; hard prompts test whether the model already knows them.
Task schema and scoring
Each task defines its inputs, answer format, and one canonical answer. An instance supplies the actual sequences and conditions. All 84 tasks use the same scorer.
- Individual task type
task_typenames one of 65 individual operations. For example,cds.translateasks for the protein encoded by a CDS.- Composition task type
composition_typenames one of 19 tasks that combine individual operations. For example,pipeline.motif_to_dnatranslates a CDS, finds a peptide motif, then maps its location back to DNA. Use this field instead oftask_typefor a composition task.- Variant
variantiseasyorhard. It changes biological reference support; both variants share the answer format and correct answer.- Answer format
output_formatisscalarfor a direct value or simple list, orjsonfor maps and records.output_rulesdefines every value’s meaning, ordering, precision, and failure form. Prompts show a compact output structure with typed placeholders. The fulloutput_schemaremains in the task metadata for automated validation.- Unique reference
objectiveandselection_ruledetermine one reference answer, including all tie-breaks. Reference solvers verify constraints, optimality, and any claim of impossibility before evaluation.- Scorer
scorer = exact_matchfor individual and composition tasks alike. It compares the complete parsed answer with the verified reference.
Each identifier has the form prefix.operation. The prefix indicates the task family or how component tasks are combined. These summaries explain the prefixes; the individual task catalogue and composition catalogue define the questions.
task_type · individual task families
| Prefix | Meaning |
|---|---|
dna | Operations on DNA bases, strand orientation, transcription, and DNA-pattern matches. |
cds | Interpret complete coding sequences, including translation, validity, and equivalence of encoded proteins. |
coords | Convert positions between DNA bases, aligned codons, and protein residues. |
variant | Apply specified DNA edits or determine their effects on the reading frame and protein product. |
ambiguity | Resolve possible codon meanings when observed DNA contains uncertain bases represented by IUPAC symbols. |
stats | Measure nucleotide composition and codon usage, across a whole CDS or within local windows. |
protein | Analyze the protein encoded by a CDS, including sequence patterns, physical properties, and cleavage products. |
rna | Analyze CDS-derived coding RNA, including edits, translation, complementarity, secondary structure, and cleavage products. |
design | Rewrite coding DNA under specified constraints while preserving its encoded protein. |
construct | Create or process engineered coding constructs, including protein changes, fused modules, tags, deletions, and cleavage products. |
library | Analyze or design mixtures of codons represented by IUPAC symbols. Here ambiguity specifies a designed mixture, rather than uncertainty about one observed sequence. |
assay | Select CDS-based primers or probes under stated sequence-matching, specificity, and uniqueness rules. |
overlap | Analyze or modify DNA read in two explicitly annotated coding windows, accounting for both encoded products. |
composition_type · pipeline and joint
| Prefix | Meaning |
|---|---|
pipeline | Several operations connected by their results. An earlier step supplies the sequence, annotation, or measurement used by later steps. Workflows can branch and can include design followed by verification. Example: Edit DNA → translate → digest. |
joint | One design evaluated against several requirements at once. The same candidate CDS must meet every constraint and any stated optimization objective; solving the component requirements separately is insufficient. Example: Remove restriction sites while enforcing GC bounds. |
Evaluating a response
- Read and validate. The answer starts on the line after a standalone
Final answer:marker and continues to the end of the response. JSON may span multiple lines. Parse the declared format and validate its fields and types against the task metadata. - Compare the contents. Apply only the declared formatting normalizations. Compare JSON objects by their keys and values, and lists in their required order. Every requested field must match, including counts and rounded numbers.
Score 1 only when both steps pass; otherwise 0. Report format compliance separately from answer accuracy. Composition tasks receive one score for the complete answer.
For example, the codon-library task expects:
{"status":"ok","codon":"GAK","residue_counts":{"D":1,"E":1}}
Reordering object keys is harmless. Changing a count, omitting a field, or choosing a different codon fails.
Shared answer conventions
An optional explanation precedes the marker. The answer itself begins on the next line and is the final part of the response. JSON is one complete object or array; indentation and line breaks are optional. Ignore surrounding whitespace and declared sequence spacing. Object-key order and equivalent numeric spellings such as 1.8500 and 1.85 do not matter. Preserve list order, multiplicities, identifiers, and values. Malformed JSON, duplicate keys, unexpected fields, and changed sequences fail validation.
Round once at the task’s specified precision, with exact halfway cases rounded away from zero; rounded negative zero becomes zero. Use declared reference constants and unrounded intermediate values. CAI optimization on a fixed-length CDS compares exact products of supplied decimal weights before taking roots or rounding.
Empty lists are []. Empty standalone sequences use EMPTY_SEQUENCE; empty sequences inside JSON use "". NONE, INVALID, and IMPOSSIBLE have the meanings defined by their tasks. JSON tasks specify their exact failure objects and use null where required.
Individual tasks (65)
Each row states what is given and what the model must do. Select a row for a task outline followed by easy and hard example prompts with complete inputs and computed answers. Format and scoring details follow the examples. Data provenance appears below each expected answer. Most examples reuse the bacterial CDS documented in Example data sources; engineered changes are identified per example. Expand Template for the unfilled version. The copy icon copies its code block verbatim. Search or filter the table to compare related tasks.
Example data sources
Most examples reuse the complete Escherichia coli K-12 MG1655 trpL CDS, a 45-base gene encoding a 14-residue leader peptide. Source: NCBI Gene 945856; locus b1265; nucleotide accession NC_000913.3, bases 1,323,038–1,323,082 on the minus strand; protein accession NP_415781.1. Retrieved 26 October 2026.
Native CDS, coding strand 5′→3′ ATG AAA GCA ATT TTC GTA CTG AAA GGT TGG TGG CGC ACT TCC TGA Protein: MKAIFVLKGWWRTS Engineered minigene: native codons 1–7 + native stop ATG AAA GCA ATT TTC GTA CTG TGA Protein: MKAIFVL
The truncated minigene keeps exact synonymous searches small enough to verify exhaustively. Each example identifies any further mutations, ambiguous codons, fusion modules, or comparison variants in its Data provenance note. Supplied RNA contacts and edits are exercises, not claims about a natural trpL structure or editing event. Codon weights are illustrative instance data, not measured expression estimates.
No matching tasks. Reset the filters or try a broader term.
CDS interpretation
Orientation, translation, coordinates, and validity.
| Task | Description | Expand details |
|---|---|---|
Reverse-complement a CDSdna.reverse_complement | Given a CDS written in one direction, write the complementary DNA strand in its own 5′→3′ direction. | |
Reverse-complement a CDSDNA strands pair in opposite directions. The question supplies a CDS as a DNA string and asks for the sequence on the opposite strand. It does not ask where another gene starts or whether the opposite strand encodes a protein. Replace every base with its DNA partner, then reverse the order so the answer is written 5′→3′. Both steps matter: complementing alone leaves the answer in the wrong direction. Role in related tasksA reverse PCR primer must be written in the orientation that binds the opposite strand. CDS-internal primer selection uses this operation to turn the end of the desired amplicon into the reverse-primer sequence. Method reference: Primer3. Task OutlineInputs. Procedure. Complement each of the 45 bases, then reverse the complete complemented string so the answer is written 5′→3′. Final answer: TCAGGAAGTGCGCCACCAACCTTTCAGTACGAAAATTGCTTTCAT Checking the answer. The answer must match the reverse complement base for base; whitespace between bases is ignored. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "dna.reverse_complement",
"output_format": "scalar",
"scorer": "exact_match",
"family": "sequence",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Make the coding RNAdna.transcribe | Given coding-strand DNA, produce its coding RNA by replacing T with U while retaining the order of the bases. | |
Make the coding RNADuring transcription, RNA polymerase copies the DNA template strand. The resulting RNA matches the opposite, coding strand except that RNA uses uracil (U) where DNA uses thymine (T). Here the supplied DNA is already that coding strand, written 5′→3′, with no introns to remove. Copy the DNA in the same order and replace every T with U. Keep the start codon and terminal stop codon in the RNA sequence. This creates the RNA input used by editing, pairing, and guide-matching tasks. Role in related tasksThis is a representation step for following specified RNA edits through to a protein and matching RNA probes against a CDS collection. It supplies the coding RNA on which those operations act; it does not reconstruct a whole transcript. Task OutlineInputs. Procedure. Copy all 45 coding-strand bases in order and replace T with U. The terminal TGA becomes UGA and remains in the RNA. Final answer: AUGAAAGCAAUUUUCGUACUGAAAGGUUGGUGGCGCACUUCCUGA Checking the answer. The complete RNA string must be correct and have the same length as the supplied CDS. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "dna.transcribe",
"output_format": "scalar",
"scorer": "exact_match",
"family": "sequence",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From specified RNA edits to protein From specified RNA edits to RNA fragments From a pairing annotation to eligible cuts Repair RNA pairs and verify the protein Balance an RNA structural constraint and codon preference Choose an RNA probe and a matched escape control Design and verify an RNA-editing-dependent product Build and audit a controlled synonymous panel From CDS collection to a minimal measurement panel | ||
Translate DNA to proteincds.translate | Given a CDS and an identified genetic code, return the protein it encodes, ending at the first in-frame stop. | |
Translate DNA to proteinThe CDS is already spliced and oriented correctly. Its first base is the first base of the annotated initiation codon, so the model need not search for an open reading frame. The named genetic code determines how each three-base codon is interpreted. Read consecutive groups of three bases. Treat the annotated initiator according to NCBI code 11, and end translation at the first stop in that reading frame. Omit the stop and all downstream sequence from the protein answer. Task OutlineInputs. Procedure. Read the 15 aligned codons from base 1: ATG starts M; the 13 subsequent sense codons complete MKAIFVLKGWWRTS; TGA ends translation and contributes no residue. Final answer: MKAIFVLKGWWRTS Checking the answer. The final amino-acid string must be exact. A correct prefix followed by extra residues is incorrect. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "cds.translate",
"output_format": "scalar",
"scorer": "exact_match",
"family": "sequence",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Other composition tasks: From peptide motif to encoding DNA From CDS to defined protein measurements From CDS panel to a diagnostic peptide From DNA edits to changed peptide readouts Assemble coding modules and locate junction motifs Design and verify an RNA-editing-dependent product | ||
Validate a complete CDScds.validate | Given a candidate complete CDS, identify specific problems with its length, initiation codon, or stop codons. | |
Validate a complete CDSThis is a check of a supplied sequence, not gene prediction. The candidate may have been damaged by an edit. A complete CDS must be long enough to contain an initiator and stop, have a length divisible by three, start with an allowed initiator, and end with a stop. Check each condition independently and report all violations. Also look for an earlier stop in the established reading frame. The formal labels below name these findings; they are not biological classes to infer from a sequence family. Task OutlineInputs. Procedure. Check the altered start, every aligned internal codon, and the last codon. The 45-base length is valid, but GCT is not an allowed initiator, codon 10 is an internal TGA, and the final GCA is not a stop. Final answer: ["internal_stop", "invalid_start", "missing_terminal_stop"] Checking the answer. The returned set of problem labels must be complete, without adding failures that the sequence does not have. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with codon 1 changed to GCT, codon 10 to TGA, and terminal codon 15 to GCA, deliberately introducing validation faults. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with codon 1 changed to GCT, codon 10 to TGA, and terminal codon 15 to GCA, deliberately introducing validation faults. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "cds.validate",
"output_format": "scalar",
"scorer": "exact_match",
"family": "sequence",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Map a nucleotide to its codoncoords.nt_to_codon | Given a nucleotide position in a CDS, identify its codon and its position within that codon. | |
Map a nucleotide to its codonThe question identifies one DNA base by its position in the supplied CDS. Because translation begins at base 1, every base in the translated region belongs to a known group of three. Count codons from 1. Within the selected codon, use offsets 0, 1, and 2 for its first, second, and third base. Return the codon number, offset, and actual three DNA bases. This provides the bookkeeping needed to connect DNA mutations to protein residues. Role in related tasksA DNA-coordinate change needs to be located within a codon before its encoded consequence can be determined. Substitution-effect classification uses that connection to identify the affected residue and compare its original and edited codons. Task OutlineInputs. Procedure. Compute floor((29−1)/3)+1 = 10 and (29−1) mod 3 = 1. Read codon 10 from bases 28–30: TGG. Final answer: {
"codon_index": 10,
"offset": 1,
"codon": "TGG"
}Checking the answer. All three returned values must identify the same supplied nucleotide. Easy exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"codon_index": <positive integer>,
"offset": <integer: 0, 1, or 2>,
"codon": <three-base DNA string>
}Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "coords.nt_to_codon",
"output_format": "json",
"scorer": "exact_match",
"family": "sequence",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Map residues back to DNAcoords.aa_to_nt | Given a range of protein residues, locate the DNA bases encoding that range in the original CDS. | |
Map residues back to DNAThe question supplies a CDS and an interval of residue positions in its translated protein. It asks where that protein segment is encoded, not where a similar DNA string happens to occur. Each residue uses three consecutive bases. Include all three bases of the first and last residues in the requested range. Both ends of the returned DNA interval are included. The initiating methionine counts as residue 1. Role in related tasksProtein-engineering requests often name residues, while the construct must be changed in DNA. This mapping identifies the codons available for a requested amino-acid substitution or the exact interval removed in a protein deletion construct. Task OutlineInputs. Procedure. Residues 9–12 span four complete codons. Their first DNA base is 3×9−2 = 25 and their last is 3×12 = 36. Final answer: [25, 36] Checking the answer. The nucleotide interval must encode exactly the requested residue interval, with neither missing nor additional codons. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "coords.aa_to_nt",
"output_format": "scalar",
"scorer": "exact_match",
"family": "sequence",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From peptide motif to encoding DNA Assemble coding modules and locate junction motifs | ||
Sequence variation
Edits, ambiguity, and equivalence.
| Task | Description | Expand details |
|---|---|---|
Apply a DNA edit scriptvariant.apply | Given a CDS and a list of DNA replacements, insertions, or deletions, return the edited DNA sequence. | |
Apply a DNA edit scriptThe question states exactly which edits to make. Every position refers to the original CDS, so an earlier insertion must not shift the coordinates used to interpret a later edit. No biological effect needs to be predicted in this task. A replacement names an inclusive interval and its new text; empty replacement text deletes that interval. An insertion names the boundary after an original base. Apply the nonoverlapping changes together and retain every unedited base. Role in related tasksApplying an edit script creates the candidate sequence that downstream checks must actually inspect. In DNA edits to peptide readouts, this step precedes translation and digestion, allowing the expected original and mutant peptide products to be compared. Task OutlineInputs. Procedure. Insert GGT after original base 24 and change original base 9 to C. Apply both instructions against the original coordinates, so the insertion does not shift the replacement’s location. Final answer: ATGAAAGCCATTTTCGTACTGAAAGGTGGTTGGTGGCGCACTTCCTGA Checking the answer. The entire edited DNA string must be correct. Whether it still encodes a valid protein is checked by other tasks. Easy exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "variant.apply",
"output_format": "scalar",
"scorer": "exact_match",
"family": "variation",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Classify a substitution effectvariant.protein_effect | Given an internal DNA substitution, determine whether it preserves the protein, changes residues, or introduces an early stop. | |
Classify a substitution effectThe supplied change replaces DNA without changing its length and does not touch the initiator or terminal stop. Translate the original and edited CDSs using the same code and reading frame. An unchanged protein is synonymous. A change to one or more amino acids without an earlier stop is missense. A new earlier stop is stop_gained and takes precedence over other residue changes. Insertions, deletions, and start-codon changes are excluded so these three answers cover every instance. Practical contextSynonymous, missense, and stop-gained are established sequence-consequence categories used by annotation tools such as Ensembl VEP. This task isolates their codon-comparison logic. The peptide-readout composition follows the sequence changes into expected digest products; neither task infers a variant’s functional impact. Method reference: Ensembl calculated variant consequences. Task OutlineInputs. Procedure. Replace Trp codon 10 TGG with TGA. Translation now ends after residue 9 instead of residue 14, so the earlier stop determines the class. Final answer: stop_gained Checking the answer. The selected category must follow from the actual translated products, rather than from the number of changed DNA bases. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "variant.protein_effect",
"output_format": "scalar",
"scorer": "exact_match",
"family": "variation",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Determine frame preservationvariant.frame_status | Given several insertions and deletions, track whether the downstream reading frame is shifted or restored after each edit. | |
Determine frame preservationAdding or removing bases changes where subsequent codon boundaries fall. A net length change divisible by three preserves the downstream grouping; a remainder of one or two shifts it. An earlier shift can be undone by a later edit. Process edit locations in their original order and keep a running total of inserted bases minus deleted bases. After each edit, report that total modulo three: 0 means the original downstream frame, while 1 and 2 indicate the two shifted phases. This does not imply that the intervening protein is unchanged. Practical contextThis check helps review engineered insertions and deletions before interpreting their protein products. Even if a later edit restores the original frame, the intervening translation may have changed. Translation and peptide comparison examines the resulting product beyond this frame-status check. Task OutlineInputs. Procedure. The C insertion after original base 9 adds one base, giving phase 1. Deleting original base 15 removes one base and restores cumulative phase 0. Final answer: {
"edits": [
{
"edit_index": 1,
"phase": 1
},
{
"edit_index": 2,
"phase": 0
}
],
"final_phase": 0
}Checking the answer. Every intermediate phase and the final phase must match the cumulative length changes. Easy exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"edits": [
{
"edit_index": <positive integer>,
"phase": <integer: 0, 1, or 2>
}
],
"final_phase": <integer: 0, 1, or 2>
}Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "variant.frame_status",
"output_format": "json",
"scorer": "exact_match",
"family": "variation",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Compare encoded proteinscds.protein_equivalence | Given two CDSs, determine whether their complete translated protein sequences are identical. | |
Compare encoded proteinsTwo different DNA sequences can encode the same protein because several codons can specify the same amino acid. DNA string equality therefore cannot answer this question. Translate both CDSs under NCBI code 11, including its initiator treatment and first-stop termination. Compare the resulting amino-acid strings, including their lengths. Return a yes/no answer; no judgement about expression or function is required. Practical contextThis is a correctness check for synonymous engineering: DNA changes are acceptable only if the encoded protein stays the same. Cloning-site removal with GC control needs this check so that manufacturing or assembly constraints do not silently alter the intended protein. Method reference: DNA Chisel examples. Task OutlineInputs. Procedure. Translate both full CDSs. GCA and GCC both encode Ala at residue 3, so both products are MKAIFVLKGWWRTS. Final answer: true Checking the answer. Both translated products must be identical for the answer to be true. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Compare native trpL with its synonymous GCA→GCC codon-3 variant. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Compare native trpL with its synonymous GCA→GCC codon-3 variant. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "cds.protein_equivalence",
"output_format": "scalar",
"scorer": "exact_match",
"family": "variation",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: Remove cloning sites while controlling GC Repair RNA pairs and verify the protein Build and audit a controlled synonymous panel | ||
Resolve an ambiguous codonambiguity.codon_set | Given an internal codon containing uncertain-base symbols, list every amino acid or stop it could encode. | |
Resolve an ambiguous codonAn IUPAC symbol can stand for several possible DNA bases. For example, N means any of A, C, G, or T. The question identifies one ambiguous codon inside an otherwise defined CDS; its possible meanings are determined by expanding those symbols. Form every concrete codon allowed by the symbols, translate each using internal codon meanings, and collect the distinct results. Report each amino acid once, even if several codons produce it. Include STOP if any expansion is a stop. Role in related tasksAn ambiguous triplet can represent uncertain base calls or a deliberately degenerate synthesis instruction. Degenerate-library enumeration uses the same expansion to establish exactly which amino acids and stops an oligonucleotide mixture could encode. Method reference: SwiftLib. Task OutlineInputs. Procedure. Expand TGN to TGA, TGC, TGG, and TGT. Their internal products are STOP, C, W, and C; remove duplicate outcomes and sort the remaining strings. Final answer: ["C", "STOP", "W"] Checking the answer. The answer must contain every possible result and no result excluded by the ambiguity symbols. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Replace native trpL codon 10 (TGG) with the ambiguous observation TGN; this denotes uncertainty, not a naturally occurring fifth base. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Replace native trpL codon 10 (TGG) with the ambiguous observation TGN; this denotes uncertainty, not a naturally occurring fifth base. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "ambiguity.codon_set",
"output_format": "scalar",
"scorer": "exact_match",
"family": "variation",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Assess an ambiguous stopambiguity.stop_certainty | Given an ambiguous internal codon, decide whether a stop is impossible, possible, or unavoidable. | |
Assess an ambiguous stopThe uncertain bases describe a set of possible concrete codons, not a probability distribution. The task asks what can be concluded about stopping from that set alone. Expand the selected codon. If none of its expansions is a stop, return never. If every expansion is a stop, return guaranteed. If both stop and non-stop expansions exist, return possible. This evaluates certainty without guessing which bases were actually present. Role in related tasksA mixed codon may produce a stop in only some synthesized molecules. This distinction matters in designing and auditing a mutagenesis library, where an apparently useful ambiguity code can also create unwanted truncated products. Method reference: SwiftLib. Task OutlineInputs. Procedure. Of the four TGN expansions, TGA is a stop and the other three are sense codons. A stop is therefore possible but not guaranteed. Final answer: possible Checking the answer. The category must account for all allowed expansions, not just one representative codon. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Replace native trpL codon 10 (TGG) with the ambiguous observation TGN; this denotes uncertainty, not a naturally occurring fifth base. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Replace native trpL codon 10 (TGG) with the ambiguous observation TGN; this denotes uncertainty, not a naturally occurring fifth base. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "ambiguity.stop_certainty",
"output_format": "scalar",
"scorer": "exact_match",
"family": "variation",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Sequence statistics
Separate, reproducible counts and numerical objectives.
| Task | Description | Expand details |
|---|---|---|
Count sense codonsstats.codon_counts | Given a CDS, count how often each DNA codon occurs in its translated region. | |
Count sense codonsThe CDS establishes the groups of three to count. This is different from counting every three-base substring: overlapping substrings between codon boundaries do not contribute. Count the initiator and all subsequent sense codons, but omit the terminal stop. Report the original DNA spellings, so synonymous codons such as GGT and GGC have separate counts even though both encode glycine. Role in related tasksCodon counts are the raw observations behind codon-usage comparisons and reference tables. Counts from a chosen reference gene set can support the preference weights used in CAI, while counts from a candidate CDS describe how its synonymous choices differ from that reference. Method reference: Codon Statistics Database. Task OutlineInputs. Procedure. Read aligned codons through residue 14. AAA and TGG each occur twice; each other reported sense codon occurs once. Exclude the final TGA. Final answer: {
"ATG": 1,
"AAA": 2,
"GCA": 1,
"ATT": 1,
"TTC": 1,
"GTA": 1,
"CTG": 1,
"GGT": 1,
"TGG": 2,
"CGC": 1,
"ACT": 1,
"TCC": 1
}Checking the answer. Each observed codon’s count must be exact; the counts must sum to the number of sense codons. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"<DNA codon>": <positive integer count>
}Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "stats.codon_counts",
"output_format": "json",
"scorer": "exact_match",
"family": "measure",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Calculate total GCstats.gc_fraction | Given a CDS, calculate the fraction of all its DNA bases that are G or C. | |
Calculate total GCGC content is a sequence-composition measurement. It counts bases across the complete supplied CDS, including its initiation and terminal stop codons. Add the number of G and C bases and divide by total sequence length. Return a fraction between 0 and 1, rounded as requested. This task does not ask whether that composition is biologically preferable. Practical contextOverall GC is a quick composition check during synthetic-gene design. Manufacturing constraints often concern local extremes as well, so windowed GC checks and synonymous GC repair turn this simple measurement into a more useful construct-design check. Method reference: Twist gene-design resources. Task OutlineInputs. Procedure. Count G and C across all 45 bases, including the initiator and terminal stop, then divide by 45 and round once to six decimal places. Final answer: 0.444444 Checking the answer. The number is checked against the calculated fraction at the stated precision. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "stats.gc_fraction",
"output_format": "scalar",
"scorer": "exact_match",
"family": "measure",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Calculate third-position GCstats.gc3_fraction | Given a CDS, calculate GC content using only the third base of each sense codon. | |
Calculate third-position GCThird codon positions are useful to examine separately because many synonymous choices differ there. The question asks for GC3, not the overall fraction of G and C in the CDS. Take the third base of every sense codon, including the initiator and excluding the terminal stop. Divide the number of those selected bases that are G or C by the number of selected bases. Other codon positions do not enter the calculation. Practical contextGC3 is used in comparative codon-usage analysis to describe compositional bias at third codon positions, where many synonymous alternatives occur. Comparing it with other codon-bias statistics helps separate a sequence’s overall compositional tendency from more specific codon preferences. Method reference: Codon Statistics Database. Task OutlineInputs. Procedure. Take the third base of each of the 14 sense codons. Seven are G or C, so GC3 is 7/14 = 0.500000. Final answer: 0.500000 Checking the answer. The answer must use the specified codon positions and denominator, with the requested rounding. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "stats.gc3_fraction",
"output_format": "scalar",
"scorer": "exact_match",
"family": "measure",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Locate GC-window violationsstats.gc_windows | Given a window length and an allowed GC range, identify local parts of a CDS whose composition falls outside that range. | |
Locate GC-window violationsA whole-CDS average can hide a short GC-rich or GC-poor region. The question therefore gives a window length: the number of consecutive DNA bases to examine at a time. It also gives the lowest and highest acceptable GC fractions. Slide that window one base at a time across the CDS and calculate GC content separately for every full window. Return the starting positions of windows below the minimum or above the maximum. Values exactly on either bound are acceptable. Practical contextA CDS can have acceptable overall GC but contain a locally extreme region that complicates synthesis or amplification. This measurement locates such regions; synonymous window repair changes them, and the cloning-and-GC composition combines that repair with assembly-site constraints. Method reference: Twist gene-design resources. Task OutlineInputs. Procedure. Slide a 12-base window by one base across the complete 45-base CDS. Count G/C in each of the 34 windows and report starts outside the inclusive 1/4–2/3 range. Final answer: [25] Checking the answer. The returned positions must identify all failing windows, including overlapping ones. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "stats.gc_windows",
"output_format": "scalar",
"scorer": "exact_match",
"family": "measure",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Calculate codon adaptation indexstats.cai | Given a CDS and codon-preference weights, calculate a codon adaptation index from those weights. | |
Calculate codon adaptation indexThe question supplies a numerical preference weight for each relevant codon. These weights define the reference against which the CDS is compared; the model is not expected to infer them from an organism name. Hosts differ in the availability of tRNAs that decode synonymous codons, which can affect translation efficiency. Highly expressed host genes provide an empirical reference for codon preferences. CAI measures resemblance to that reference, giving one guide for designing a gene for expression in that host. Broader methods such as LinearDesign combine CAI with RNA folding models to optimize codon usage and structural stability together. Look up the weight of each sense codon after the initiator and take their geometric mean. The initiator and terminal stop are excluded. The geometric mean combines preference across the sequence while retaining sensitivity to poorly weighted codons. Task OutlineInputs. Procedure. Read the six internal minigene codons and look up each supplied weight. Multiply those six values, take the sixth root, then round once; the initiator and terminal stop have no weight in this calculation. Final answer: 0.584804 Checking the answer. The calculated value must use the supplied weights and specified codon exclusions. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Supplied illustrative codon weights; these are not measured E. coli adaptation or expression estimates. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Supplied illustrative codon weights; these are not measured E. coli adaptation or expression estimates. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "stats.cai",
"output_format": "scalar",
"scorer": "exact_match",
"family": "measure",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Find nucleotide patternsdna.motif_positions | Given a DNA pattern, locate every matching interval in the CDS on the requested strand or strands. | |
Find nucleotide patternsRestriction enzymes recognize particular DNA sequences: for example, EcoRI recognizes GAATTC. That is one concrete reason to locate a short pattern in a CDS. The pattern is supplied here and may include IUPAC symbols allowing several bases at a position. Check every possible starting position, including starts that cross codon boundaries and overlap other matches. If both strands are requested, also search for the reverse-complement pattern. Report all intervals on the coordinate axis of the original CDS, with the matching strand. Role in related tasksLocating restriction-enzyme recognition sites is a routine prerequisite for cloning-site cleanup. Motif removal uses these hits to eliminate unwanted sites, including sites crossing codon boundaries, while preserving the protein. Method reference: GoldenMutagenesis domestication. Task OutlineInputs. Procedure. Search the forward DNA for TGG and for its reverse complement CCA. Report every match in original forward coordinates, including the two adjacent Trp codons. Final answer: [
{
"start": 28,
"end": 30,
"strand": "+"
},
{
"start": 31,
"end": 33,
"strand": "+"
}
]Checking the answer. Every matching interval and strand must be present. Identical hits from a palindromic pattern are reported only once. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"start": <positive integer>,
"end": <positive integer>,
"strand": <"+" or "-">
}
]Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "dna.motif_positions",
"output_format": "json",
"scorer": "exact_match",
"family": "measure",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Protein analysis
Patterns, properties, and peptide readouts derived from CDS.
| Task | Description | Expand details |
|---|---|---|
Find a supplied peptide patternprotein.motif_positions | Translate the CDS and find every protein segment matching a supplied amino-acid pattern. | |
Find a supplied peptide patternA supplied peptide pattern can describe a real enzyme-recognition site. For example, TEV protease cleavage uses ENLYFQG in this benchmark. More general patterns can name an exact residue, allow any residue, list alternatives, or exclude selected residues. Match the pattern at every protein position and return the residue intervals of complete matches. Include overlaps. This identifies a sequence pattern only; it does not require recognizing a protein family or deciding whether a matched site is functional. Role in related tasksAn explicitly supplied peptide pattern can mark a protease site or an engineered sequence feature. Motif-to-DNA mapping locates its encoding codons for a later edit, and motif removal changes a permitted occurrence. The task does not infer a motif’s function from its sequence. Task OutlineInputs. Procedure. Translate the R12N variant to MKAIFVLKGWWNTS. Test each three-residue window for N, then a residue other than P, then S or T. NTS at 12–14 is the match. Final answer: [[12, 14]] Checking the answer. The result must include exactly the matching residue intervals, numbered from the protein’s first residue. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with codon 12 CGC→AAT (R12N), creating the NTS sequence used to illustrate sequon matching; no actual glycosylation is asserted. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with codon 12 CGC→AAT (R12N), creating the NTS sequence used to illustrate sequon matching; no actual glycosylation is asserted. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.motif_positions",
"output_format": "scalar",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From peptide motif to encoding DNA Assemble coding modules and locate junction motifs | ||
Locate N-glycosylation sequonsprotein.nglyco_sequons | Translate the CDS and identify protein positions matching the conventional N-glycosylation sequon pattern. | |
Locate N-glycosylation sequonsN-linked glycosylation attaches a sugar chain to an asparagine side chain in a protein. Its common acceptor pattern is asparagine, then any residue except proline, then serine or threonine: N–X–S/T with X≠P. A matching three-residue sequence is called a sequon. Find every occurrence of that three-residue pattern and report the position of its first residue. Do not decide whether the protein reaches a cellular compartment where glycosylation occurs or whether a particular site is actually modified. Practical contextSequon scanning identifies candidate sites to inspect when designing or reviewing a protein for N-glycosylation studies. It is a sequence screen: actual modification depends on the expression system and protein context. Residue-to-DNA mapping can locate the codons if a candidate site is selected for mutagenesis. Method reference: PROSITE N-glycosylation pattern. Task OutlineInputs. Procedure. Translate the R12N variant and scan for N–non-P–S/T. NTS begins at residue 12; report its start. This establishes a sequence match, not actual glycosylation. Final answer: [12] Checking the answer. All matching start positions must be correct, including overlapping matches. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with codon 12 CGC→AAT (R12N), creating the NTS sequence used to illustrate sequon matching; no actual glycosylation is asserted. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with codon 12 CGC→AAT (R12N), creating the NTS sequence used to illustrate sequon matching; no actual glycosylation is asserted. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.nglyco_sequons",
"output_format": "scalar",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Count amino acidsprotein.residue_counts | Translate a CDS and count the number of each amino acid in its protein product. | |
Count amino acidsThis measures protein composition rather than DNA composition or codon usage. Different synonymous codons contribute to the same amino-acid count after translation. Translate the CDS, then count each residue in the resulting protein. Include the initiating methionine and do not count the stop. Return counts for residues that occur; the order of residues in the protein is not part of this answer. Role in related tasksComposition counts supply inputs to mass, charge, and isoelectric-point calculations. The protein-measurements composition connects a CDS to these descriptors, which can support product identification and purification planning. Task OutlineInputs. Procedure. Translate to MKAIFVLKGWWRTS and increment one count per residue. K and W each contribute two occurrences; every other observed residue contributes one. Final answer: {
"M": 1,
"K": 2,
"A": 1,
"I": 1,
"F": 1,
"V": 1,
"L": 1,
"G": 1,
"W": 2,
"R": 1,
"T": 1,
"S": 1
}Checking the answer. The residue counts must be exact and sum to the translated protein’s length. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"<one-letter amino-acid symbol>": <positive integer count>
}Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.residue_counts",
"output_format": "json",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Calculate peptide massprotein.monoisotopic_mass | Translate a CDS and calculate the neutral monoisotopic mass of its unmodified protein product. | |
Calculate peptide massMass calculations depend on a chemical convention. This task specifies an unmodified linear protein with free ends, without removing the initiator or forming disulfide bonds. Monoisotopic mass uses the masses of the specified isotopes rather than an average over isotopes. A chain of n amino acids has n−1 peptide bonds; its chemical composition differs from n free amino acids by n−1 water molecules. The tabulated residue masses already subtract one water per residue. Sum those residue masses and add one water to recover the complete chain with free ends. Each separate digestion product gets its own water contribution. Practical contextTheoretical peptide masses help interpret mass-spectrometry measurements when checking a protein’s identity or processing. Tag assembly, cleavage, and mass calculation applies this to the actual cleavage products, where a retained tag or cleavage scar changes the expected mass. Method reference: ExPASy PeptideMass documentation. Task OutlineInputs. Procedure. Translate the 14-residue leader peptide. Add the supplied monoisotopic residue masses and one water molecule for the complete unmodified linear peptide, then round to four decimal places. Final answer: 1721.9440 Checking the answer. The declared residue-mass sum plus one water must round to the reported four-decimal mass. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.monoisotopic_mass",
"output_format": "scalar",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From CDS to defined protein measurements Build a tagged construct, cleave it, measure products | ||
Calculate mean hydropathyprotein.mean_hydropathy | Translate a CDS and average the encoded residues’ scores on the Kyte–Doolittle hydropathy scale. | |
Calculate mean hydropathyAmino-acid side chains differ in how favorably they interact with water. The Kyte–Doolittle hydropathy scale assigns experimentally informed scores to that tendency: positive values are more hydrophobic, while negative values are more hydrophilic. These are a published scale, not arbitrary scores invented for this task. Look up the score for each residue and calculate the ordinary arithmetic mean across the whole protein. This is a summary measurement; it is not a request to classify the protein as a transporter or predict its location. Practical contextMean hydropathy is a standard descriptive property reported by tools such as ProtParam. It summarizes overall residue composition; hydropathy analyses that seek local hydrophobic segments use positional windows instead. Here it belongs in a protein-characterization report, rather than serving as a standalone membrane-localization prediction. Method reference: ExPASy ProtParam documentation. Task OutlineInputs. Procedure. Translate the 14-residue leader peptide, add its 14 Kyte–Doolittle scores, and divide by 14. Count both Lys and both Trp residues in the mean. Final answer: 0.2143 Checking the answer. The answer must use the named scale and average all translated residues with equal weight. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.mean_hydropathy",
"output_format": "scalar",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Digest with trypsin rulesprotein.trypsin_digest | Translate the CDS and list the peptide fragments produced by a specified complete trypsin-cleavage model. | |
Digest with trypsin rulesTrypsin is a real protein-digesting enzyme used to generate peptides for mass spectrometry. Its specificity favors cutting after lysine (K) or arginine (R). The benchmark uses the familiar simplified rule: cut after K/R unless the following residue is proline (P). Actual cleavage efficiencies and exceptions are not calculated. Apply the rule at every eligible bond, allowing no missed cuts, and retain fragments at both ends. Return fragments in their original order, together with their inclusive residue intervals in the original protein. Practical contextIn-silico digestion predicts peptide sequences to compare with proteomics measurements. Diagnostic-peptide selection looks for products that distinguish related proteins, while variant-to-peptide comparison shows how a sequence change alters the expected digest. Method reference: ExPASy PeptideMass documentation. Task OutlineInputs. Procedure. Translate to MKAIFVLKGWWRTS. Cut after K2, K8, and R12. This gives MK, AIFVLK, GWWR, and TS; retain the nonempty final TS fragment. Final answer: [
{
"start": 1,
"end": 2,
"peptide": "MK"
},
{
"start": 3,
"end": 8,
"peptide": "AIFVLK"
},
{
"start": 9,
"end": 12,
"peptide": "GWWR"
},
{
"start": 13,
"end": 14,
"peptide": "TS"
}
]Checking the answer. Both peptide sequences and their original residue intervals must be correct. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"start": <positive integer>,
"end": <positive integer>,
"peptide": <amino-acid string>
}
]Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.trypsin_digest",
"output_format": "json",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From CDS panel to a diagnostic peptide From DNA edits to changed peptide readouts | ||
Select a distinguishing peptideprotein.diagnostic_peptide | From a target CDS and comparison CDSs, choose a digest peptide that occurs only in the target’s protein. | |
Select a distinguishing peptideYou are given a target CDS encoding the protein you want to identify, and comparison CDSs encoding other proteins you want to distinguish it from. The comparison set is called the background in the input fields. Translate and digest each sequence using the same trypsin rule. An identifying peptide must occur in the target digest and in none of the comparison digests. Keep target peptides whose lengths lie within the supplied minimum and maximum. Select the shortest eligible peptide, using alphabetical order to break a tie. Return NONE if none qualifies. Uniqueness applies only to the supplied comparison set, not an entire proteome. Practical contextA peptide unique to one candidate protein is a starting point for choosing an identifying mass-spectrometry readout. The CDS-panel composition derives such candidates from actual digests. Subsequent assay design must also consider whether the peptide can be detected reliably, not just whether its sequence is unique. Method reference: ExPASy PeptideMass documentation. Task OutlineInputs. Procedure. The target digest is MK, AIFVLK, GWWR, TS. The I4V comparison changes only AIFVLK to AVFVLK. Remove shared peptides and apply the length limits; AIFVLK is the qualifying target-only sequence. Final answer: AIFVLK Checking the answer. The selected peptide must satisfy panel uniqueness and length limits, and obey the stated selection order. Detectability in a mass spectrometer is not scored. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL is the target. The comparison is a designed I4V variant (codon 4 ATT→GTT), not a second natural accession. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL is the target. The comparison is a designed I4V variant (codon 4 ATT→GTT), not a second natural accession. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionFrom eligible target-only peptide sequences, choose the shortest, then the ASCII-lexicographically smallest sequence. Multiple copies of one sequence do not create separate choices. If no target-only peptide meets the length limits, return: NONE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.diagnostic_peptide",
"output_format": "scalar",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "From eligible target-only peptide sequences, choose the shortest, then the ASCII-lexicographically smallest sequence. Multiple copies of one sequence do not create separate choices."
} | ||
Calculate model charge at a pHprotein.charge_at_ph | Translate a CDS and estimate its protein’s net charge at a specified pH using supplied ionization parameters. | |
Calculate model charge at a pHSome amino-acid side chains and the two ends of a protein gain or lose protons as pH changes. The question supplies a pH and pKa values, which determine the fractions of sites treated as charged in the declared calculation. Count each relevant acidic or basic side chain and both free termini, calculate its contribution with the Henderson–Hasselbalch relation, and add the contributions. The model treats sites independently; it does not account for a folded protein changing a site’s environment. Practical contextEstimated protein charge helps choose a pH and resin type for ion-exchange purification, which separates molecules through charge-dependent binding. This calculation supplies a first estimate from the sequence; purification methods then test suitable buffers and binding conditions. Method reference: Cytiva ion-exchanger selection guide. Task OutlineInputs. Procedure. At pH 7, add the fractional positive charges of the N terminus, two Lys residues, and one Arg, then subtract the fractional negative C-terminal charge. Use the supplied pKa values and round the total once. Final answer: 2.9095 Checking the answer. The net charge must match the supplied-pKa model at the requested pH and precision. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.charge_at_ph",
"output_format": "scalar",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Calculate the isoelectric point (pI)protein.isoelectric_point | Translate a CDS, then find the pH where the protein’s calculated positive and negative charges cancel. | |
Calculate the isoelectric point (pI)The isoelectric point (pI) is the pH at which a protein’s positive and negative charges balance, giving a total charge of zero. The inputs are a CDS and pKa values for the groups that can carry charge. A group’s pKa is the pH at which its calculated contribution is half of its fully charged value. The charge calculation is a fixed arithmetic approximation: treat each group separately and add its contribution. Count one N terminus, one C terminus, and each occurrence of the listed amino-acid side chains. Use the supplied pKa for each group in the formulas below; all other side chains contribute zero. Increasing pH decreases this calculated total charge. Each instance is chosen so positive and negative contributions cancel once between pH 0 and pH 14. Those two pH numbers are the initial search bounds.
Simple algorithm: repeatedly halve the pH range
Practical contextA protein’s pI helps select conditions for ion-exchange purification and isoelectric focusing. Together with charge at a chosen pH, it indicates which side of the charge transition an operating condition lies on, before testing the behavior experimentally. Method reference: Cytiva ion-exchanger selection guide. Task OutlineInputs. Procedure. Evaluate the same charge sum while varying pH from 0 to 14. Bisect that range, keeping the side containing zero charge after each step, and round the pH of the zero crossing to two decimal places. Final answer: 11.67 Checking the answer. Find the unique zero-charge pH under the supplied pKa values and formulas, then round it to two decimal places. That rounded value is the reference answer. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "protein.isoelectric_point",
"output_format": "scalar",
"scorer": "exact_match",
"family": "protein",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Coding RNA analysis
Editing, pairing, cleavage, and sequence targeting.
| Task | Description | Expand details |
|---|---|---|
Apply specified RNA editsrna.apply_edits | Transcribe a CDS, apply explicitly listed changes to its coding RNA, and return the edited RNA sequence. | |
Apply specified RNA editsRNA editing changes RNA after transcription. One real example is APOBEC1-mediated C-to-U editing of apolipoprotein B mRNA: a CAA codon becomes the UAA stop codon, producing a shorter protein. Here the editing positions and replacement bases are supplied, rather than predicted from an enzyme’s recognition preferences. Apply all changes using positions in that original RNA, keeping RNA’s U alphabet. Replacement text may also insert or delete bases. Later edit coordinates are not shifted by earlier changes. Translation of the edited product is a separate component. Role in related tasksWhen RNA-editing events have been measured or explicitly proposed, their consequences must be evaluated on the edited sequence. Edit-to-protein analysis uses this step to establish the transcript that is translated; edit-to-fragment analysis instead derives a possible RNA sequence-QC readout. Task OutlineInputs. Procedure. Transcribe the R12Q variant, then replace original RNA base 34 C with U. Codon 12 changes from CAA to UAA, but this task returns the entire edited RNA rather than translating it. Final answer: AUGAAAGCAAUUUUCGUACUGAAAGGUUGGUGGUAAACUUCCUGA Checking the answer. The complete edited RNA must match the specified changes and preserve every unedited base. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with R12Q (CGC→CAA), followed by a supplied C→U editing instruction at RNA base 34. This is a constructed editing exercise, not an observed trpL edit. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with R12Q (CGC→CAA), followed by a supplied C→U editing instruction at RNA base 34. This is a constructed editing exercise, not an observed trpL edit. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.apply_edits",
"output_format": "scalar",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From specified RNA edits to protein From specified RNA edits to RNA fragments Design and verify an RNA-editing-dependent product | ||
Translate coding RNArna.translate | Translate coding RNA derived from a CDS, including RNA that has undergone supplied edits. | |
Translate coding RNAThis component accepts RNA rather than DNA so an edited transcript can be passed directly into translation. In an isolated prompt, the RNA is transcribed from the supplied CDS; in a composition, it can be the output of the RNA-editing task. Read RNA codons from the established first base using the named genetic code, with U in place of DNA’s T. Stop at the first in-frame stop and omit that stop from the answer. Do not silently switch back to translating the original DNA. Role in related tasksThe useful distinction from direct DNA translation appears in the RNA-editing composition: the protein must be derived from the edited coding RNA, which can differ from the product predicted from the original DNA. This task supplies that downstream translation step. Task OutlineInputs. Procedure. Replace coding-strand T with U and read codons from base 1 under code 11. The coding RNA gives the same MKAIFVLKGWWRTS protein as the DNA translation task. Final answer: MKAIFVLKGWWRTS Checking the answer. The returned protein must come from the actual RNA input, including its edits and stopping point. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.translate",
"output_format": "scalar",
"scorer": "exact_match",
"family": "rna",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From specified RNA edits to protein Design and verify an RNA-editing-dependent product | ||
Check specified RNA pairsrna.pair_compatibility | Given a CDS-derived RNA and specified paired positions, identify pairs whose bases cannot form an allowed pair. | |
Check specified RNA pairsComplementary stretches of one RNA can bind each other, forming paired stems and unpaired loops. A–U and C–G are the canonical base-pair types. The supplied position pairs state which contacts to check; the task does not discover the fold. Read the two bases at each listed pair and test their compatibility. Real RNA can also form G–U wobble pairs, but this benchmark deliberately permits only A–U and C–G in either direction. Return the incompatible position pairs only. Role in related tasksThis is a local consistency check after changing bases in a proposed RNA stem. Pair repair with protein verification uses it to test whether a synonymous redesign restores the requested contacts. The structure is supplied, so the check does not establish that those contacts form experimentally. Task OutlineInputs. Procedure. Look up both RNA bases for each supplied pair. Pairs (4,13) and (5,12) are A–U; (7,15) is G–C; (25,33) is G–G and is the sole incompatible pair. Final answer: [[25, 33]] Checking the answer. The answer must identify every incompatible supplied pair. It does not assert that the RNA actually adopts the supplied structure. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Pairs are supplied test annotations, not an experimentally determined RNA structure. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Pairs are supplied test annotations, not an experimentally determined RNA structure. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.pair_compatibility",
"output_format": "scalar",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Decode a pairing maprna.dotbracket_to_pairs | Convert a supplied dot-bracket annotation for coding RNA into explicit pairs of nucleotide positions. | |
Decode a pairing mapDot-bracket notation describes an RNA pairing map. A dot marks an unpaired base; matching opening and closing parentheses identify a pair. The annotation has the same length as the RNA. Match the parentheses and report their 1-based positions. Nested pairs are allowed, but this task excludes crossing pairs called pseudoknots. This is notation interpretation rather than prediction of a structure from the sequence. Role in related tasksDot-bracket notation is a common output of RNA structure software. Converting it to coordinate pairs makes the annotation usable in explicit sequence checks, such as pair compatibility and the simplified structure-dependent cleavage model. Method reference: ViennaRNA. Task OutlineInputs. Procedure. Read the 45-character annotation left to right. Push each opening-parenthesis position onto a stack; pair each closing parenthesis with the most recent unmatched opening position. Sort the five resulting pairs. Final answer: [[4, 13], [5, 12], [6, 11], [25, 36], [26, 34]] Checking the answer. Every parenthesis pair must become exactly one correct coordinate pair. Easy exampleNative CDS: E. coli K-12 MG1655 trpL, locus Dot-bracket is a supplied illustrative noncrossing annotation, not a measured structure. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard exampleNative CDS: E. coli K-12 MG1655 trpL, locus Dot-bracket is a supplied illustrative noncrossing annotation, not a measured structure. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.dotbracket_to_pairs",
"output_format": "scalar",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Digest coding RNA with RNase T1 rulesrna.t1_digest | Transcribe a CDS and split its RNA into fragments using an RNase T1 rule, optionally restricted by a supplied pairing map. | |
Digest coding RNA with RNase T1 rulesRNase T1 is a real guanosine-specific RNA-cutting enzyme originally obtained from the fungus Aspergillus oryzae. It cleaves the RNA backbone immediately after G, on the G’s 3′ side. The G therefore remains at the end of the upstream fragment. Choosing G reflects this enzyme’s biochemical specificity. RNase T1 acts preferentially on single-stranded RNA. The question either treats every G as eligible or uses a supplied pairing map to allow cuts only at unpaired G bases. Complete cleavage and that fixed accessibility mask are benchmark simplifications. Scan for eligible cuts, split the sequence, and return the fragments in sequence order with their original RNA coordinates. When a pairing map is supplied, keep it fixed rather than refolding after each cut. Practical contextRNase fragment mapping is used in RNA sequence characterization, including mRNA quality control. This task supplies the simple sequence-to-fragments step. Practical mapping combines digestion with mass spectrometry and may use complementary or partial digests to resolve fragments that a single complete digest cannot distinguish. Method reference: RNA and mRNA sequence mapping by mass spectrometry. Task OutlineInputs. Procedure. Transcribe all 45 bases and cut immediately after each G, the specificity of RNase T1 in this benchmark. Every position is accessible; retain every nonempty fragment and its original RNA coordinates. Final answer: [
{
"start": 1,
"end": 3,
"fragment": "AUG"
},
{
"start": 4,
"end": 7,
"fragment": "AAAG"
},
{
"start": 8,
"end": 16,
"fragment": "CAAUUUUCG"
},
{
"start": 17,
"end": 21,
"fragment": "UACUG"
},
{
"start": 22,
"end": 25,
"fragment": "AAAG"
},
{
"start": 26,
"end": 26,
"fragment": "G"
},
{
"start": 27,
"end": 29,
"fragment": "UUG"
},
{
"start": 30,
"end": 30,
"fragment": "G"
},
{
"start": 31,
"end": 32,
"fragment": "UG"
},
{
"start": 33,
"end": 33,
"fragment": "G"
},
{
"start": 34,
"end": 35,
"fragment": "CG"
},
{
"start": 36,
"end": 44,
"fragment": "CACUUCCUG"
},
{
"start": 45,
"end": 45,
"fragment": "A"
}
]Checking the answer. The fragments must reflect both the cleavage rule and the requested accessibility setting. Experimental digestion efficiency is not part of the score. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus All positions are accessible in this example; the separate structure-gated digest uses a supplied pairing map. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus All positions are accessible in this example; the separate structure-gated digest uses a supplied pairing map. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"start": <positive integer>,
"end": <positive integer>,
"fragment": <RNA string>
}
]Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.t1_digest",
"output_format": "json",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: From specified RNA edits to RNA fragments From a pairing annotation to eligible cuts | ||
Match an RNA guiderna.guide_hits | Given an RNA guide and a CDS-derived RNA, find target intervals complementary to the guide within an allowed mismatch count. | |
Match an RNA guideGuide-directed recognition is real biology: Argonaute proteins use guide RNAs to recognize complementary mRNA in RNA silencing. The two RNAs pair in opposite directions, so compare target windows with the reverse complement of the supplied 5′→3′ guide. Examine every target window as long as the guide. Count unequal positions and retain windows at or below the given maximum. This is a simplified sequence screen: real guide systems distinguish mismatch positions and structural contexts, while this task uses a uniform mismatch count with no gaps or wobble. Role in related tasksComplementary-hit screening helps identify candidate RNA probes or target-site changes. Probe selection uses the hits for sequence discrimination, and guide-escape design uses them to disrupt a specified interaction. Broader oligonucleotide design methods also model binding thermodynamics and competing structures. Method reference: NUPACK documentation. Task OutlineInputs. Procedure. Reverse-complement the 21-base guide, compare it with each of the 25 equal-length RNA windows, and count mismatches. The designed matching window spans bases 7–27. Final answer: [
{
"target_start": 7,
"target_end": 27,
"mismatches": 0
}
]Checking the answer. Return all qualifying intervals and their mismatch counts. Sequence compatibility does not establish cellular guide activity. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus The 21-base guide is designed as the reverse complement of coding-RNA bases 7–27; it is not an experimentally validated reagent. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus The 21-base guide is designed as the reverse complement of coding-RNA bases 7–27; it is not an experimentally validated reagent. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"target_start": <positive integer>,
"target_end": <positive integer>,
"mismatches": <nonnegative integer>
}
]Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.guide_hits",
"output_format": "json",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: Choose an RNA probe and a matched escape control From CDS collection to a minimal measurement panel | ||
Count coding-RNA patternsrna.motif_counts | Transcribe the CDS and count occurrences of specified short RNA sequences, including overlapping occurrences. | |
Count coding-RNA patternsThe question supplies literal RNA patterns to measure, such as a two-base sequence or a longer recognition pattern. No recognition motif needs to be inferred from biological context. Check every possible RNA starting position for each pattern. Include matches crossing codon boundaries, and report a count of zero when a supplied pattern is absent. This gives a simple measurement that synonymous-design tasks can control. Role in related tasksA pattern can be a probe’s exact complementary target sequence; counting it measures how many such candidate sites are present. Probe selection adds comparison RNAs, while motif control changes the count through synonymous recoding. Arbitrary patterns have no biological interpretation until a recognition process or experiment is named. Method reference: NUPACK documentation. Task OutlineInputs. Procedure. Search separately for each exact RNA pattern, moving one base at a time. Count both adjacent UGG codons and the spanning UGGUGG occurrence; include zero for an absent requested pattern. Final answer: {
"CGCG": 0,
"AAA": 2,
"UGG": 2,
"UGGUGG": 1
}Checking the answer. Each supplied pattern must have its exact occurrence count, including overlaps. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"<supplied RNA pattern>": <nonnegative integer count>
}Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.motif_counts",
"output_format": "json",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Score a specified RNA structurerna.structure_score | Given a coding RNA, a pairing map, and numerical pair scores, calculate the score of that particular structure. | |
Score a specified RNA structureBoth the structure and its scoring table are supplied. The task therefore does not require finding a fold or knowing which structure is most stable in a cell. First check that every listed pair is allowed and that no base is assigned two partners. If valid, add the supplied score for each pair. Return INVALID if the map violates those conditions. The additive score is a declared toy objective, not thermodynamic free energy. Exercise scopeRNA base pairing is physical, but the numerical bonuses in this task are supplied exercise scores. Joint RNA-and-codon optimization uses them as an exactly checkable constraint. Practical methods such as LinearDesign use thermodynamic energy models that include stacking and loops, rather than assigning an arbitrary bonus to each isolated pair. Method reference: LinearDesign. Task OutlineInputs. Procedure. Read bases at the four listed contacts. Two A–U contacts score 2 each and two G–C contacts score 3 each. No position is reused; add 2+2+3+3. Final answer: 10 Checking the answer. The validity judgement and, when valid, the total must be exact. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Pair map and integer scores are supplied benchmark inputs, not a folding-energy model or measured structure. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Pair map and integer scores are supplied benchmark inputs, not a folding-energy model or measured structure. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
If a listed pair is noncanonical or a position is reused, return: INVALID Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.structure_score",
"output_format": "scalar",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: Balance an RNA structural constraint and codon preference | ||
Find a maximum-pair RNA foldrna.max_pair_fold | Find a noncrossing arrangement of complementary base pairs in a CDS-derived RNA, with as many pairs as possible. | |
Find a maximum-pair RNA foldChoose which positions in the coding RNA pair with each other. Pairing means complementary bases: A with U, or C with G; G–U wobble is excluded. Each base can have at most one partner, pairs cannot cross, and paired positions must satisfy the supplied minimum-loop value. Two stretches of the same RNA align in opposite directions. In an uninterrupted stem, the second stretch is the reverse complement of the first when both are written 5′→3′. For example, The minimum-loop value is the number of positions that must lie between the endpoints of any pair. Search for the largest possible number of pairs under these rules and return a dot-bracket representation. This is a small algorithmic folding model, not a claim about the RNA’s physical structure. Exercise scopeThis follows the historical Nussinov approach to RNA folding: choose compatible, noncrossing base pairs by combining solutions for shorter sequence segments. The backbone geometry motivates restrictions on very short loops. Maximizing pair count is a deliberate simplification; thermodynamic methods additionally account for stacking and loop energies. Method references: Nussinov and colleagues: Algorithms for Loop Matchings, ViennaRNA. Task OutlineInputs. Procedure. Use interval dynamic programming: either leave a base unpaired or pair it with each permitted complementary partner, combining the best inside and remaining intervals. Maximize pair count, then choose the first full annotation in the stated character order. Final answer: (.(((.((((((((...)...)))..))).((...)))))).).. Checking the answer. The structure must have the maximum allowed pair count and be the first optimal dot-bracket string under the declared ASCII order. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus The answer optimizes the stated complementary-pair count; it is not a claim about the in vivo trpL RNA fold. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus The answer optimizes the stated complementary-pair count; it is not a claim about the in vivo trpL RNA fold. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionMaximize the allowed pair count first. Among optimal structures, choose the ASCII-lexicographically smallest full dot-bracket string, comparing characters in the order opening parenthesis, closing parenthesis, then dot. Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "rna.max_pair_fold",
"output_format": "scalar",
"scorer": "exact_match",
"family": "rna",
"domain": "rna",
"objective": "maximize canonical pair count",
"selection_rule": "Maximize the allowed pair count first. Among optimal structures, choose the ASCII-lexicographically smallest full dot-bracket string, comparing characters in the order opening parenthesis, closing parenthesis, then dot."
} | ||
Synonymous redesign
Synonymous design across DNA and RNA constraints.
| Task | Description | Expand details |
|---|---|---|
Rewrite with a specified number of DNA changesdesign.synonymous_distance | Rewrite a CDS to encode the same protein while changing a requested number of DNA positions. | |
Rewrite with a specified number of DNA changesThe question supplies a CDS and a permitted range for the number of changed bases. This range is the edit budget: it counts DNA positions whose letters differ between the original and rewritten sequences, not the number of codons touched. Use synonymous codons to satisfy that range while keeping the complete protein unchanged. The first and terminal stop codons stay fixed, and no bases may be inserted or deleted. This isolates how much DNA sequence can change without changing the encoded product. Exercise scopeAn exact number of DNA changes has no inherent biological benefit. The useful component is enforcing an edit budget while preserving a protein: joint RNA-and-codon optimization uses that constraint while pursuing a separate sequence-design objective. Task OutlineInputs. Procedure. Enumerate the 1,152 synonymous minigene encodings with fixed terminal codons. Keep only sequences differing from the input at one or two bases, then choose the first whole DNA string in A<C<G<T order. Final answer: ATGAAAGCAATATTCGTACTATGA Checking the answer. The changed-position count must lie within the supplied inclusive range, with protein and fixed codons preserved. Select the first feasible DNA string under the stated order; this need not use the fewest edits. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.synonymous_distance",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "multi",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
}Used in: Balance an RNA structural constraint and codon preference | ||
Rewrite using permitted codonsdesign.codon_allowlist | Replace internal codons with synonymous alternatives drawn only from a supplied permitted list. | |
Rewrite using permitted codonsThe question supplies a list of DNA codons that may be used at internal protein-coding positions. This can model removing selected codons from a construct while leaving the amino-acid sequence intact. For each internal residue, choose an allowed codon that encodes the same amino acid. Keep the first and terminal stop codons unchanged. If a required amino acid has no permitted encoding at a necessary position, report that the requested rewrite is impossible. Practical contextDNA Chisel can exclude codons that are rare in a chosen host. That provides a concrete source for an allowlist: retain the other synonymous codons while preserving the protein. The host reference or design policy must be supplied; an excluded codon is not intrinsically undesirable in every organism. Method reference: DNA Chisel specifications. Task OutlineInputs. Procedure. At each of the six internal positions, intersect the supplied allowed codons with synonymous choices. Compare the complete permitted DNA strings and choose the first in the stated order. Final answer: ATGAAGGCCATTTTCGTGCTGTGA Checking the answer. Every internal codon must be allowed, and the complete protein must remain identical. The selected sequence must also satisfy the declared tie-break. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.codon_allowlist",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "dna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Optimize supplied codon preferencesdesign.codon_preference | Choose synonymous internal codons to maximize a supplied codon-preference score while retaining the protein. | |
Optimize supplied codon preferencesThe question provides positive numerical weights for codons. These are the preference system for this particular instance; there is no need to infer a host’s preferences or predict expression. For each internal sense position, choose a synonymous codon to maximize the defined codon adaptation index. The first and terminal stop codons are fixed. This simple version has no additional structure or motif constraints; those enter explicitly in compositions. Practical contextThis is the design counterpart of codon adaptation measurement: choose synonymous codons according to a host-derived preference reference when preparing a gene for expression. The joint-design composition adds an RNA constraint; methods such as LinearDesign extend that idea using a thermodynamic folding objective. Method reference: LinearDesign. Task OutlineInputs. Procedure. Evaluate the product of the six internal codon weights for each synonymous encoding. Maximizing that product also maximizes its sixth-root CAI; break any tie by the complete DNA string. Final answer: ATGAAAGCGATTTTCGTGCTGTGA Checking the answer. The candidate must encode the original protein and achieve the highest possible score. The selected sequence must also satisfy the declared tie-break. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Weights are supplied illustrative preferences, not measured host expression data. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Weights are supplied illustrative preferences, not measured host expression data. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAfter achieving the stated optimum, break ties by the lexicographically smallest full DNA string, with A<C<G<T. Compare objective values before rounding. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.codon_preference",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "dna",
"objective": "maximize supplied-weight CAI",
"selection_rule": "After achieving the stated optimum, break ties by the lexicographically smallest full DNA string, with A<C<G<T. Compare objective values before rounding."
} | ||
Match positional codon-preference rangesdesign.codon_profile | Rewrite internal codons so each position meets its own supplied codon-preference range, while preserving the protein. | |
Match positional codon-preference rangesA single whole-CDS average does not specify where high- or low-preference codons occur. This task instead supplies preference weights and a separate acceptable weight interval for each internal codon position. Choose a synonymous codon whose weight lies inside that position’s interval. A request can deliberately retain lower-preference positions rather than optimizing every position upward. The ranges are supplied design targets, not something the model must infer from a natural expression pattern. Practical contextCodon harmonization methods, such as CHARMING, try to reproduce a local pattern of codon usage when adapting a gene to another host, rather than maximizing every codon’s preference. The supplied positional ranges make that design idea testable here; they are a codon-usage proxy, not measured translation speeds. Method reference: CHARMING. Task OutlineInputs. Procedure. For each internal position, retain synonymous codons whose individual weight is inside that position’s supplied range. Combine the choices and select the first complete DNA string; do not average the ranges. Final answer: ATGAAGGCGATATTCGTACTGTGA Checking the answer. Every positional interval must be satisfied, with the protein and terminal codons preserved. Report IMPOSSIBLE if no assignment exists. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Weights and positional ranges are supplied illustrative inputs. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Weights and positional ranges are supplied illustrative inputs. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.codon_profile",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "dna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Control local GC by recodingdesign.gc_windows | Synonymously rewrite a CDS so every local DNA window has GC content within a supplied range. | |
Control local GC by recodingThe question gives a window length and a minimum and maximum GC fraction. These define local composition requirements rather than a single whole-gene target. Change internal codons without changing the protein, then check every full window one base at a time across the final DNA. Overlapping windows couple the choices: fixing one region can create a problem in its neighbor. The first and terminal stop codons remain fixed. Practical contextSynthetic-gene design often needs to reduce local GC extremes while keeping the encoded product fixed. The cloning-and-GC composition combines this requirement with restriction-site removal, reflecting the simultaneous sequence constraints handled by practical construct-design tools. Method references: Twist gene-design resources, DNA Chisel examples. Task OutlineInputs. Procedure. The original minigene violates the stricter GC bounds. For each synonymous candidate, check every one of its 16 nine-base windows against the inclusive 3/9–4/9 range. Choose the first DNA string that passes every window. Final answer: ATGAAAGCAATCTTCGTACTATGA Checking the answer. The same final CDS must pass every window and preserve the original protein. A good average GC value alone is insufficient. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.gc_windows",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "dna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Remove specified DNA motifsdesign.remove_dna_motifs | Remove every occurrence of specified DNA patterns using synonymous changes, preserving the encoded protein. | |
Remove specified DNA motifsA construct may contain a recognition site for an enzyme that will be used during cloning. For example, EcoRI recognizes GAATTC, the site in the worked example. The question supplies the unwanted patterns and whether to search the coding strand alone or both strands. Change internal codons synonymously until every forbidden occurrence is absent from the final CDS. Search across codon boundaries as well as within codons, and check that the edits did not create a new copy elsewhere. Preserve the first and terminal stop codons. Practical contextGolden Gate assembly requires removing unwanted internal recognition sites for the Type IIS enzyme being used; otherwise the insert can be cut internally. This synonymous cleanup is often called domestication. The combined design task also controls GC while removing the sites. Method reference: GoldenMutagenesis domestication. Task OutlineInputs. Procedure. Search each synonymous candidate for GAATTC on both strands, including matches across codon boundaries. Discard any candidate containing the EcoRI recognition site and select the first surviving full DNA string. Final answer: ATGAAAGAATTTTTCGTACTATGA Checking the answer. The candidate must preserve the protein and contain no forbidden hits under the requested strand rule. The selected sequence must also satisfy the declared tie-break. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3E and I4F substitutions (GCA→GAA, ATT→TTC), creating the real EcoRI recognition sequence GAATTC at bases 7–12. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3E and I4F substitutions (GCA→GAA, ATT→TTC), creating the real EcoRI recognition sequence GAATTC at bases 7–12. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.remove_dna_motifs",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "dna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
}Used in: Remove cloning sites while controlling GC Encode a protein change and remove cloning sites | ||
Introduce a DNA recognition sitedesign.insert_dna_motif | Create a specified DNA recognition sequence at a requested CDS position through synonymous changes. | |
Introduce a DNA recognition siteA restriction-enzyme recognition site can be introduced as a marker for screening an engineered sequence. The worked example uses EcoRI’s real GAATTC site. The input specifies the literal recognition sequence and the DNA position where it must begin. Choose synonymous internal codons so the required bases appear at the requested location, even if the site spans several codons. Other copies of the site are allowed in this version. Keep the first and terminal stop codons fixed. Practical contextIntroducing a synonymous restriction site can create a convenient way to screen an engineered allele by restriction digestion. This task isolates site creation without changing the protein. Motif scanning can then confirm where the recognition sequence occurs. Method reference: Restriction-site markers in engineered alleles. Task OutlineInputs. Procedure. Require GAATTC exactly at DNA bases 7–12 while preserving the protein. This fixes codons 3–4 to GAA TTC; choose the first complete synonymous encoding satisfying that site. Final answer: ATGAAAGAATTCTTCGTACTATGA Checking the answer. The required site must appear at the specified start and all protein-preservation conditions must hold. Otherwise return IMPOSSIBLE. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Use the same A3E/I4F cloning substrate, with synonymous GAA→GAG at codon 3 removing the EcoRI site before the task. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Use the same A3E/I4F cloning substrate, with synonymous GAA→GAG at codon 3 removing the EcoRI site before the task. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.insert_dna_motif",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "dna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Break homopolymers and repeatsdesign.break_repeats | Use synonymous substitutions to remove overly long runs of one base and excessive repeated DNA substrings. | |
Break homopolymers and repeatsThe question gives the longest permitted run of identical bases and limits on how many times a substring of a given length may occur. These are sequence-design requirements supplied for the instance. Recode internal codons without changing the protein. Count runs and repeated substrings across the entire final CDS, including codon junctions and overlapping occurrences. The first and terminal stop codons cannot be changed. Practical contextLong homopolymers and repeated sequences can make DNA synthesis and amplification more difficult. Synonymous recoding can reduce that sequence complexity without changing the protein. The benchmark’s explicit repeat rules represent one part of the broader manufacturability screening used by synthesis providers. Method reference: Twist gene-design resources. Task OutlineInputs. Procedure. For each synonymous minigene, check the longest identical-base run and count all overlapping three-base substrings. Reject runs longer than two and any triplet appearing more than twice, then choose the first valid DNA string. Final answer: ATGAAGGCAATATTCGTACTATGA Checking the answer. Every repeat limit must hold on the final sequence while translation stays unchanged. Satisfying only the homopolymer limit is not enough when substring limits are also supplied. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.break_repeats",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "dna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Control coding-RNA motifsdesign.rna_motif_control | Synonymously rewrite DNA so its coding RNA contains specified numbers of supplied RNA patterns. | |
Control coding-RNA motifsThe patterns are RNA strings using U, and each comes with an acceptable minimum and maximum number of occurrences. This can request removing a pattern, introducing one, or controlling its copy count. Choose synonymous DNA codons, transcribe the candidate, and count each RNA pattern in that final RNA. Include overlapping matches and matches crossing codon boundaries. Keep the protein and first and terminal stop codons unchanged. Exercise scopeIf a supplied pattern is a probe’s exact complementary target, synonymous recoding can remove that candidate binding sequence while preserving the protein. Guide-escape design extends this idea to near-matches. Dinucleotide control provides another concrete composition target; a generic unnamed pattern remains an abstract constraint. Method reference: NUPACK documentation. Task OutlineInputs. Procedure. Transcribe each synonymous candidate and count all overlapping AAA and AAG occurrences, including codon junctions. Require zero AAA and exactly one AAG, then apply the DNA-order tie-break. Final answer: ATGAAGGCAATATTCGTACTATGA Checking the answer. All pattern counts must fall within their supplied ranges on the same final RNA, while the encoded protein is preserved. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.rna_motif_control",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "rna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Control RNA dinucleotide countsdesign.dinucleotide_counts | Synonymously rewrite a CDS to meet requested counts of adjacent RNA-base pairs such as CG or UA. | |
Control RNA dinucleotide countsA dinucleotide is simply two consecutive bases along a sequence, not a structural base pair. CpG means a C followed by G; UpA means U followed by A. The question gives acceptable counts for selected RNA dinucleotides. Change synonymous DNA codons and count adjacent pairs in the resulting coding RNA at every position. A pair spanning two codons counts just like a pair inside a codon. Keep the protein and first and terminal stop codons fixed. Practical contextDinucleotide composition can affect how cellular factors recognize RNA; for example, ZAP recognizes CpG-containing RNA. A controlled synonymous panel uses count changes to construct testable comparisons while preserving protein identity and total GC. The count is an experimental design variable, rather than a prediction of an effect’s size. Method reference: Origin and evolution of the zinc finger antiviral protein. Task OutlineInputs. Procedure. The input has only one CG. Count adjacent bases in each candidate’s coding RNA and require exactly two CG occurrences and exactly one GC occurrence. Select the first complete synonymous DNA string passing both counts. Final answer: ATGAAAGCGATATTCGTACTATGA Checking the answer. Every requested dinucleotide count must lie within its stated range in the final coding RNA. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.dinucleotide_counts",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "rna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Repair pairing synonymouslydesign.pairing_repair | Use synonymous CDS changes to make specified positions in its coding RNA form allowed base pairs. | |
Repair pairing synonymouslyThe question supplies the intended RNA pairs and the DNA positions that may be edited. A mismatch in the supplied map is known in advance; the model does not have to discover the structure or identify a biological compensatory mutation. Choose changes at the permitted positions so every listed RNA pair becomes canonical, while the CDS still encodes its original protein. The first and terminal stop codons remain fixed. A change that repairs one pair but changes an amino acid is not a valid repair here. Practical contextThis has a direct experimental precedent: a study of bacterial rpsT mRNA found that some fitness costs of synonymous mutations could be compensated by second synonymous changes restoring predicted base pairing. Repair and verification isolates the sequence-design logic: restore the proposed RNA contact without changing the encoded protein. Method reference: Synonymous mutations and restoration of mRNA base pairing. Task OutlineInputs. Procedure. RNA base 3 is G and base 9 is initially A. Change only DNA base 9: Ala codon GCA can become GCC without changing the protein, replacing the incompatible G–A contact with G–C. Final answer: ATGAAAGCCATTTTCGTACTGTGA Checking the answer. All specified pairs must be compatible, all DNA changes permitted, and the protein unchanged. The selected sequence must also satisfy the declared tie-break. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The supplied pair (3,9) is initially G–A; the only permitted DNA position is the third base of Ala codon 3. The map is an illustrative repair target. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The supplied pair (3,9) is initially G–A; the only permitted DNA position is the third base of Ala codon 3. The map is an illustrative repair target. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.pairing_repair",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "rna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Optimize a fixed RNA pairing scoredesign.structure_score | Choose synonymous codons to maximize or minimize a supplied score for a fixed coding-RNA pairing map. | |
Optimize a fixed RNA pairing scoreThe RNA position pairs are fixed by the question. A numerical table assigns values to allowed pair types, and the question says whether to make their total larger or smaller. This is not a request to predict folding free energy. Search synonymous versions of the CDS, preserving the first and terminal stop codons. Every required pair must remain canonical. Among feasible candidates, choose one whose total pair score is optimal in the requested direction. Exercise scopeThis is an optimization exercise over a supplied map and artificial pair scores. The joint-design composition tests whether the solver can satisfy that objective alongside codon and edit constraints. Practical mRNA design uses richer folding objectives, as illustrated by LinearDesign. Method reference: LinearDesign. Task OutlineInputs. Procedure. RNA positions 9 and 18 are the third bases of codons 3 and 6. Enumerate compatible synonymous choices, sum the supplied score for their fixed contact, maximize that score, and use the complete DNA string to break ties. Final answer: ATGAAAGCCATATTCGTGCTATGA Checking the answer. The final CDS must preserve the protein, satisfy every pair, and attain the optimum under the supplied score table. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Positions 9 and 18 are synonymous third bases. The fixed pair map and scores are supplied test inputs. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Positions 9 and 18 are synonymous third bases. The fixed pair map and scores are supplied test inputs. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAfter achieving the stated optimum, break ties by the lexicographically smallest full DNA string, with A<C<G<T. Compare objective values before rounding. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.structure_score",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "rna",
"objective": "direction over fixed-map additive pair score",
"selection_rule": "After achieving the stated optimum, break ties by the lexicographically smallest full DNA string, with A<C<G<T. Compare objective values before rounding."
} | ||
Disrupt a specified local hairpindesign.expose_rna_window | Synonymously change a CDS to break specified RNA stem pairs that involve a selected region. | |
Disrupt a specified local hairpinThe question supplies a candidate pairing map, an RNA interval of interest, and the DNA positions that may change. It asks for disruption of the listed stem pairs touching that region, rather than discovery of all possible alternative structures. Make permitted synonymous substitutions so every relevant listed pair becomes incompatible under the no-wobble pairing rule. Pairs outside the selected region need not be broken. Preserve the protein and fixed terminal codons. Exercise scopeA complementary probe must compete with bases already paired inside its target RNA. Disrupting a proposed stem is therefore a first step toward designing an accessible binding region. Practical methods also evaluate alternative folds and binding energies; this task checks only the supplied contacts. Method reference: NUPACK documentation. Task OutlineInputs. Procedure. Of the three supplied A–U stem contacts, only (5,12) touches the target base 12. Change the Ile codon ATT to ATA at its third position: that contact becomes A–A while the encoded protein stays unchanged. Final answer: ATGAAAGCAATATTCGTACTGTGA Checking the answer. All targeted listed pairs must be broken without an unauthorized DNA or protein change. Passing does not establish physical accessibility if the RNA can adopt an unlisted fold. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The supplied three-pair stem initially consists of A–U contacts (4,13), (5,12), and (6,11). Expose base 12 by altering its synonymous codon position; this is not a prediction of the natural fold. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The supplied three-pair stem initially consists of A–U contacts (4,13), (5,12), and (6,11). Expose base 12 by altering its synonymous codon position; this is not a prediction of the natural fold. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.expose_rna_window",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "rna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Create a guide-escape controldesign.guide_escape | Create a synonymous CDS whose coding RNA no longer closely matches a supplied RNA guide. | |
Create a guide-escape controlThe question supplies a guide, permitted DNA-edit locations, and the minimum number of mismatches required between that guide and every potential RNA target window. This can define a matched sequence-recognition control that encodes the same protein. Change only permitted DNA positions using synonymous choices, then compare every same-length RNA window with the guide’s reverse complement. The mismatch minimum must hold everywhere, so removing the original best match must not create another close match nearby. Keep the terminal codons fixed. Practical contextSynonymous changes are used to make RNAi-resistant rescue constructs: the same protein is reintroduced from RNA that escapes the knockdown reagent, helping test whether a phenotype came from loss of that protein. The matched-target composition captures the sequence-design step; reagent activity still requires experimental testing. Method reference: RNAi-resistant rescue in a B-cyclin study. Task OutlineInputs. Procedure. Compare the fixed 21-base guide’s reverse complement with every 21-base window of each permitted synonymous candidate. Require at least two mismatches in every window and select the first whole DNA string that passes. Final answer: ATGAAAGCAATATTCGTACTATGA Checking the answer. The candidate must preserve the protein and meet the mismatch minimum at every window. The task makes no claim about actual resistance to an RNA-targeting reagent. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Guide is a designed 21-base reverse complement of minigene RNA bases 4–24, not a validated biological reagent. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Guide is a designed 21-base reverse complement of minigene RNA bases 4–24, not a validated biological reagent. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.guide_escape",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "rna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Build a controlled synonymous paneldesign.variant_panel | Generate several synonymous CDSs with different requested RNA CG counts but the same total number of G/C bases. | |
Build a controlled synonymous panelThe question asks for a matched collection, not one optimized sequence. Every member must encode the original protein. Each has its own target number of adjacent CG occurrences in coding RNA, while all share one required total G+C count. Choose distinct synonymous sequences satisfying those counts exactly. This creates a simple controlled comparison: CG occurrence count varies while protein identity and overall GC composition are held fixed. It does not claim to hold every other RNA property constant. Practical contextMatched synonymous panels let experiments compare RNA abundance or protein output while keeping the encoded protein fixed. Here CG count is the intended variable and total GC is additionally controlled. The audit composition verifies those properties; it does not assume other RNA features remain identical. Method reference: Coding-sequence determinants of expression. Task OutlineInputs. Procedure. Enumerate synonymous minigenes with the required total G/C count. Group them by overlapping RNA CG count, then choose a distinct member for each requested count in input order. Apply the whole-panel tie-break. Final answer: ["ATGAAAGCAATATTTGTACTATGA", "ATGAAAGCAATATTCGTATTATGA"] Checking the answer. Every member must meet its assigned CG count and the common GC count, and all must preserve the protein and terminal codons. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong complete feasible panels, choose the lexicographically smallest list of DNA strings: compare the first differing member using A<C<G<T. Resolve choices across the whole panel, including distinctness; do not choose each member independently. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "design.variant_panel",
"output_format": "scalar",
"scorer": "exact_match",
"family": "redesign",
"domain": "multi",
"objective": "none",
"selection_rule": "Among complete feasible panels, choose the lexicographically smallest list of DNA strings: compare the first differing member using A<C<G<T. Resolve choices across the whole panel, including distinctness; do not choose each member independently."
} | ||
Protein and construct design
Mutations, libraries, tags, and coding modules.
| Task | Description | Expand details |
|---|---|---|
Encode a requested amino-acid substitutionconstruct.minimal_aa_edit | Change one requested protein residue by replacing its DNA codon with as few base substitutions as possible. | |
Encode a requested amino-acid substitutionThe question identifies an internal residue and the amino acid it should become. Unlike synonymous redesign, this task deliberately changes the protein at that one position. Consider codons encoding the requested amino acid and choose the one differing from the original codon at the fewest bases. Only that codon may change. If several choices use the same number of changes, select the alphabetically first DNA codon. Practical contextThis is the sequence-design part of site-directed mutagenesis: encode a chosen amino-acid replacement with as few nucleotide substitutions as possible. The protein-editing and cloning composition also removes unwanted assembly sites, turning the residue-level request into a more usable construct sequence. Method reference: Site-directed mutagenesis protocol. Task OutlineInputs. Procedure. At residue 3, compare each Val codon with the original Ala codon GCA. GTA changes one base and encodes V; choose among minimum-change candidates by the DNA-order rule. Final answer: ATGAAAGTAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCTGA Checking the answer. The intended residue must change, every other base must stay fixed, and the chosen codon must satisfy the minimum-change and tie-breaking rules. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionMinimize the total number of changed nucleotides permitted by this task; among equally minimal candidates, return the lexicographically smallest full DNA string (A<C<G<T). If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "construct.minimal_aa_edit",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "minimize changed nucleotides",
"selection_rule": "Minimize the total number of changed nucleotides permitted by this task; among equally minimal candidates, return the lexicographically smallest full DNA string (A<C<G<T)."
} | ||
Remove a protein motifconstruct.remove_peptide_motif | Modify permitted protein residues to remove a specified peptide pattern, then return DNA encoding the modified product. | |
Remove a protein motifThe question supplies an unwanted literal amino-acid sequence and a list of protein positions that may change, with the allowed replacement residues at each position. It does not ask which natural mutations would preserve function. Choose permitted amino-acid changes until the unwanted pattern is absent from the complete protein. Encode that product in a CDS while retaining its first and terminal stop codons. A change can remove one occurrence but create another, so the final product must be checked globally. Practical contextAn unwanted protease recognition sequence can interfere with processing an engineered protein. This task removes a specified motif under explicit amino-acid permissions. Motif-to-DNA mapping identifies the encoding codons; the allowed changes must be chosen by the experiment, since motif removal alone cannot establish preserved protein function. Method reference: ExPASy PeptideCutter. Task OutlineInputs. Procedure. The minigene encodes MKAIFVL and contains KA at residues 2–3. Use only the permitted A3G substitution to remove that pattern, then choose the first DNA encoding of the allowed final protein. Final answer: ATGAAAGGAATATTCGTACTATGA Checking the answer. The resulting protein must obey every residue permission and contain no forbidden pattern. Retained activity or folding is not part of this task. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "construct.remove_peptide_motif",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Build a tagged protein CDSconstruct.tag_fusion | Assemble a CDS encoding a supplied tag and linker at a specified end of the original protein. | |
Build a tagged protein CDSA tag is a supplied coding module added to a protein construct, often to support purification or detection. The question gives the DNA for the tag and linker, so the model does not invent their sequences. Follow the explicit assembly convention. For an N-terminal tag, retain the original initiating codon, then add tag and linker before the remaining original sense codons. For a C-terminal tag, append linker and tag after the original sense codons. Keep one final stop. Practical contextA concrete affinity tag is His6: six histidines that bind nickel affinity material, allowing the attached protein to be captured during purification. The supplied tag and linker DNA encode such modules. The tag-cleavage composition follows a removable tag through processing and calculates the resulting product masses. Method reference: His6-tagged protein purification. Task OutlineInputs. Procedure. Keep the native initiator, insert the supplied His6–TEV tag and GGS linker, then append the unchanged native sequence from codon 2 through its terminal stop. Final answer: ATGCATCATCATCATCATCATGAAAATCTGTATTTTCAGGGTGGTTCTAAAGCAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCTGA Checking the answer. The constructed DNA must contain the modules in the required order and preserve their reading frame, with no unintended sequence changes. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus The supplied modules encode a His6 tag followed by a TEV site (HHHHHHENLYFQ) and a GGS linker. These are designed additions to native trpL. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus The supplied modules encode a His6 tag followed by a TEV site (HHHHHHENLYFQ) and a GGS linker. These are designed additions to native trpL. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "construct.tag_fusion",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: Build a tagged construct, cleave it, measure products | ||
Derive TEV-cleaved productsconstruct.tev_products | Translate a constructed CDS and determine the protein fragments remaining after the specified TEV cleavage. | |
Derive TEV-cleaved productsTEV protease is a real enzyme derived from tobacco etch virus and widely used to remove engineered affinity tags. ENLYFQG is a common cleavage-site sequence; the cut is ENLYFQ|G. The benchmark fixes this exact site even though the actual enzyme accepts some additional sequences. Locate all complete recognition sites and split the protein at their cleavage bonds. The G belongs to the downstream fragment. Return every fragment in its original order rather than automatically discarding the tag or reporting only a preferred product. Practical contextTEV protease is used to remove affinity tags after protein purification. Predicting the products establishes what tag sequence or cleavage scar remains on the target. The cleavage-and-mass composition uses those exact sequences when deriving an expected identity readout. Method reference: Removal of affinity tags with TEV protease. Task OutlineInputs. Procedure. Translate the tagged native construct. Find ENLYFQG and cut ENLYFQ|G, leaving the GGS linker on the downstream fragment. Retain the two nonempty protein fragments in their original order. Final answer: ["MHHHHHHENLYFQ", "GGSKAIFVLKGWWRTS"] Checking the answer. The fragments must reconstruct the original protein when joined and place each cleavage at the stated bond. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL after inserting His6–TEV-site tag DNA CATCATCATCATCATCATGAAAATCTGTATTTTCAG and GGS linker GGTGGTTCT immediately after its initiator. This is the same construct produced by tag_fusion and tag_cleave_mass. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL after inserting His6–TEV-site tag DNA CATCATCATCATCATCATGAAAATCTGTATTTTCAG and GGS linker GGTGGTTCT immediately after its initiator. This is the same construct produced by tag_fusion and tag_cleave_mass. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "construct.tev_products",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Used in: Build a tagged construct, cleave it, measure products | ||
Enumerate a degenerate codon librarylibrary.codon_products | Expand an ambiguous internal DNA codon and count how many concrete codons encode each amino acid or stop. | |
Enumerate a degenerate codon libraryDegenerate oligonucleotide synthesis mixes nucleotide choices at selected positions, producing a pool of DNA sequences for mutagenesis experiments. IUPAC notation describes those choices compactly: N, for example, permits A/C/G/T. The question asks which protein alternatives such a mixed codon covers at one CDS position. Expand all possible base combinations and translate each codon internally. Count concrete codons per amino acid, rather than reporting each amino acid once. These are combinatorial counts, not measured library frequencies or expression levels. Practical contextBefore ordering a degenerate oligonucleotide, library designers need to know which amino acids it covers, how redundantly it encodes them, and whether it includes stops. Library design and verification uses this enumeration to audit a proposed mixed-codon design. Method reference: SwiftLib. Task OutlineInputs. Procedure. Expand NNK into 4×4×2 = 32 distinct DNA codons and translate each internally. Increment the corresponding amino-acid or STOP count once per concrete codon, including outcomes outside the native Ala residue. Final answer: {
"A": 2,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 2,
"H": 1,
"I": 1,
"K": 1,
"L": 3,
"M": 1,
"N": 1,
"P": 2,
"Q": 1,
"R": 3,
"S": 3,
"STOP": 1,
"T": 2,
"V": 2,
"W": 1,
"Y": 1
}Checking the answer. The residue and stop counts must account for every concrete codon in the expansion exactly once. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Replace native Ala codon 3 with NNK to represent a designed 32-codon saturation library. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Replace native Ala codon 3 with NNK to represent a designed 32-codon saturation library. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"<one-letter amino-acid symbol or STOP>": <positive integer count>
}Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "library.codon_products",
"output_format": "json",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Design a focused degenerate codonlibrary.design_codon | Choose an ambiguous DNA codon that covers requested amino acids without encoding stops, while limiting unwanted alternatives. | |
Design a focused degenerate codonThe question supplies the amino acids desired at one internal CDS position. One IUPAC triplet may cover those choices compactly, but its expansion can also include additional amino acids. Search triplets whose concrete codons cover every requested residue and none of the stops. Prefer the fewest extra amino-acid types, then the fewest concrete codons. A final alphabetical tie-break makes the answer unique. If no triplet can satisfy stop-free coverage, return IMPOSSIBLE. Practical contextFocused mutagenesis libraries target selected amino acids while limiting how many variants must be screened. Degenerate-codon optimization tools such as SwiftLib address that trade-off. The design-and-audit composition checks the resulting codon mixture’s actual coverage instead of relying on its intended target set. Method reference: SwiftLib. Task OutlineInputs. Procedure. Enumerate all 15³ IUPAC triplets, expand each into concrete codons, and discard stops or incomplete A/G/V coverage. Minimize extra amino-acid types, then expansion size, then the IUPAC string. Final answer: GBA Checking the answer. Coverage and stop avoidance are mandatory. The answer must also achieve the declared ordering of the optimization criteria. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionRequire target-residue coverage and no stops. Minimize extra amino-acid types, then the number of concrete codons, then the IUPAC triplet in ASCII order A<B<C<D<G<H<K<M<N<R<S<T<V<W<Y. Compare the symbols themselves, not their expanded nucleotide sets. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "library.design_codon",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "lexicographic objective: extra residue types, concrete codons, triplet",
"selection_rule": "Require target-residue coverage and no stops. Minimize extra amino-acid types, then the number of concrete codons, then the IUPAC triplet in ASCII order A<B<C<D<G<H<K<M<N<R<S<T<V<W<Y. Compare the symbols themselves, not their expanded nucleotide sets."
} | ||
Delete a protein intervalconstruct.inframe_deletion | Remove a specified range of protein residues by deleting exactly the corresponding complete DNA codons. | |
Delete a protein intervalThe question identifies an internal residue interval in the protein encoded by a CDS. The goal is to remove that segment without shifting the grouping of downstream codons. Map the residue interval to DNA, delete those complete codons, and leave all other DNA unchanged. The interval excludes the initiating residue, and the original terminal stop is retained. Practical contextDeletion constructs can test the contribution of an explicitly chosen protein region. This task turns those residue boundaries into an in-frame DNA deletion. It prepares the sequence for such a comparison; deciding whether the shortened protein still folds or functions requires evidence beyond the deletion operation. Method reference: Site-directed mutagenesis protocol. Task OutlineInputs. Procedure. Remove complete codons 8–9, DNA bases 22–27, without changing the order or identities of any remaining bases. Keep the original initiator and terminal TGA. Final answer: ATGAAAGCAATTTTCGTACTGTGGTGGCGCACTTCCTGA Checking the answer. Exactly the requested codons must be deleted; synonymous changes elsewhere are not allowed in this task. Easy exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard exampleNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "construct.inframe_deletion",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Join coding modulesconstruct.join_modules | Join two supplied CDSs with a coding linker to make one continuous fusion-protein CDS. | |
Join coding modulesThe question gives two complete coding sequences and a linker made of complete, stop-free codons. Joining the DNA naively would retain the first CDS’s stop and prevent translation into the second module. Remove the first CDS’s terminal stop and the second CDS’s initiating codon. Join the remaining first module, linker, and second module, retaining the first initiator and the second terminal stop. This fixes precisely which residues appear at the junction. Practical contextFusion constructs combine a target protein with reporters, tags, or other supplied coding modules. Correct reading frame and stop handling are essential at each join. The junction-audit composition then checks whether assembly created an unwanted peptide motif across a module boundary. Method reference: Addgene bacterial expression collection. Task OutlineInputs. Procedure. Remove only the full-length module’s final TGA and the minigene module’s initial ATG. Join the remaining modules around the supplied GGS linker, retaining the first module’s initiator and the second’s stop. Final answer: ATGAAAGCAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCGGTGGTTCTAAAGCAATTTTCGTACTGTGA Checking the answer. The fused DNA must follow that exact junction convention and preserve all remaining module bases. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Join native full-length trpL to the explicitly truncated trpL minigene using a designed GGS linker. This is a constructed tandem fusion, not a natural gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Join native full-length trpL to the explicitly truncated trpL minigene using a designed GGS linker. This is a constructed tandem fusion, not a natural gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "construct.join_modules",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "protein",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Design an RNA-editing-dependent productconstruct.edit_aware_encoding | Design a synonymous CDS whose coding RNA produces a requested different protein after explicitly specified RNA edits. | |
Design an RNA-editing-dependent productThe question supplies an original CDS, fixed RNA editing events, a desired post-edit protein, and the DNA positions that may change. Before editing, the designed DNA must still encode the original protein. Choose permitted synonymous codons that make those particular RNA edits yield the desired product. Check two branches: translation before editing and translation after transcription plus editing. Editing sites and enzyme behavior are given, not predicted. Exercise scopeADAR enzymes convert RNA adenosine to inosine, which is often read as G during translation. The example represents that recoding as A→G and asks for a synonymous DNA encoding with different unedited and edited proteins. This is a two-state sequence exercise: the editing event is assumed, not evidence that ADAR will act at the chosen site. Method reference: Programmable editing by endogenous ADAR. Task OutlineInputs. Procedure. The unedited codon 3 must still encode Ser. Change TCT to AGT using the two permitted DNA positions; the supplied RNA edit then changes AGU to GGU, encoding the required Gly. Final answer: ATGAAAAGTATTTTCGTACTGTGA Checking the answer. One designed CDS must pass both protein requirements and every DNA-edit restriction. An answer that changes the unedited protein is invalid. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3S (GCA→TCT). The supplied RNA edit sets base 7 to G; choose a synonymous Ser encoding so that this edit yields Gly. No naturally observed editing is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3S (GCA→TCT). The supplied RNA edit sets base 7 to G; choose a synonymous Ser encoding so that this edit yields Gly. No naturally observed editing is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "construct.edit_aware_encoding",
"output_format": "scalar",
"scorer": "exact_match",
"family": "construct",
"domain": "rna",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Assay design
CDS-targeted primers and discriminating probe panels.
| Task | Description | Expand details |
|---|---|---|
Choose CDS-internal PCR primersassay.primer_pair | Choose forward and reverse DNA primers for a specified interval entirely within a supplied CDS. | |
Choose CDS-internal PCR primersThe question fixes the desired amplified interval and primer length. It also supplies acceptable GC fractions. The primers must bind the intended ends in opposing directions; no genomic flanks need to be supplied. Take the first primer-length bases of the interval for the forward primer. Reverse-complement the last primer-length bases for the reverse primer. Check both composition limits and uniqueness of their intended oriented binding sites within this CDS. Practical contextCorrect primer orientation and target endpoints are prerequisites for amplifying a CDS segment. This task isolates that sequence-selection step. Practical tools such as Primer3 also evaluate melting temperatures, self-complementarity, and interactions between primers when choosing a pair for an assay. Method reference: Primer3. Task OutlineInputs. Procedure. Take native bases 1–18 as the forward primer. Reverse-complement bases 28–45 for the reverse primer. Check both GC fractions and confirm that each binding sequence occurs once in the supplied CDS. Final answer: {
"status": "ok",
"forward": "ATGAAAGCAATTTTCGTA",
"reverse": "TCAGGAAGTGCGCCACCA"
}Checking the answer. Both sequences must have the correct orientation and interval endpoints and satisfy the supplied constraints. Melting behavior and genome-wide specificity are outside this version. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"status": "ok",
"forward": <DNA string>,
"reverse": <DNA string>
}
If either fixed primer fails the supplied checks, return: {
"status": "impossible",
"forward": null,
"reverse": null
}Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "assay.primer_pair",
"output_format": "json",
"scorer": "exact_match",
"family": "assay",
"domain": "dna",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Select a CDS-specific RNA probeassay.select_rna_probe | Choose a complementary RNA probe that matches the target CDS’s RNA but differs sufficiently from every supplied background RNA. | |
Select a CDS-specific RNA probeThe question supplies a target CDS, comparison CDSs, a probe length, and a required minimum mismatch count against backgrounds. This defines specificity relative to a stated panel rather than the whole transcriptome. Find a target window and take its reverse complement as the probe. Reject it if any same-length background window is too close a match. Among passing probes choose the alphabetically first RNA sequence. Only exact-length, ungapped comparisons are used. Practical contextRNA fluorescence in situ hybridization detects transcripts using labeled oligonucleotide probes that bind complementary RNA sequences. This task isolates the candidate-specificity screen against supplied CDS-derived RNAs. Binding strength, competing structures, and detection chemistry require additional assay design. Method references: Imaging individual mRNA molecules with labeled probes, NUPACK documentation. Task OutlineInputs. Procedure. Enumerate reverse complements of every 12-base target window. Reject probes having an exact complementary window in the I4V comparison, then choose the first remaining RNA string in A<C<G<U order. Final answer: AAAAUUGCUUUC Checking the answer. The probe must perfectly complement a target window and meet the mismatch minimum everywhere in every background. Report IMPOSSIBLE if no probe qualifies. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Comparison is a designed I4V minigene variant (ATT→GTT). Probes and escape changes are computed design exercises, not validated reagents. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Comparison is a designed I4V minigene variant (ATT→GTT). Probes and escape changes are computed design exercises, not validated reagents. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionChoose the lexicographically smallest qualifying probe sequence in RNA order A<C<G<U. A probe occurring at several target positions remains one sequence choice. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "assay.select_rna_probe",
"output_format": "scalar",
"scorer": "exact_match",
"family": "assay",
"domain": "rna",
"objective": "none",
"selection_rule": "Choose the lexicographically smallest qualifying probe sequence in RNA order A<C<G<U. A probe occurring at several target positions remains one sequence choice."
} | ||
Distinguish CDSs with a probe panelassay.min_probe_panel | Select the smallest subset of supplied RNA probes whose match patterns distinguish every CDS in a supplied collection. | |
Distinguish CDSs with a probe panelEach candidate probe gives a binary measurement: it either has an exact complementary match in a CDS-derived RNA or it does not. Several probes together give each RNA a pattern of positive and negative results. Choose probes so no two RNAs have the same resulting pattern. Minimize the number chosen; use the specified probe-ID ordering to break ties. This is a measurement-selection problem, not a request to predict hybridization efficiency. Practical contextChoosing a small set of informative probes can reduce the number of measurements needed to distinguish candidate RNAs. The sequence-to-panel composition supplies the match matrix. This is the combinatorial selection stage, using ideal binary hits rather than measured hybridization performance. Task OutlineInputs. Procedure. For every candidate probe, record exact complementary hits in the three CDS-derived RNAs. Enumerate probe subsets by size, require three different hit signatures, and apply the probe-ID tie-break. Final answer: ["trpL_A3_window", "trpL_R12_window"] Checking the answer. Every RNA must have a unique signature and the panel must use the minimum possible number of probes. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Panel order: native trpL, synonymous Ala3 GCA→GCC variant, synonymous Arg12 CGC→CGT variant. Candidate 12-base probes are designed reverse complements of native windows 4–15, 28–39, and 16–27. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Panel order: native trpL, synonymous Ala3 GCA→GCC variant, synonymous Arg12 CGC→CGT variant. Candidate 12-base probes are designed reverse complements of native windows 4–15, 28–39, and 16–27. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionMinimize the number of selected probes, then choose the lexicographically smallest sorted list of probe IDs. Compare complete ID strings in ASCII order. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "assay.min_probe_panel",
"output_format": "scalar",
"scorer": "exact_match",
"family": "assay",
"domain": "rna",
"objective": "minimize number of probes",
"selection_rule": "Minimize the number of selected probes, then choose the lexicographically smallest sorted list of probe IDs. Compare complete ID strings in ASCII order."
} | ||
Overlapping reading frames
Explicitly annotated overlaps and coupled constraints.
| Task | Description | Expand details |
|---|---|---|
Evaluate a change in two framesoverlap.compare_products | Given two annotated coding windows and a DNA substitution, compare the before-and-after peptide in each window. | |
Evaluate a change in two framesOverlapping coding information occurs naturally. In the human CDKN2A locus, p16INK4a and p14ARF use different reading frames in a shared exon. One DNA edit can therefore affect two encoded products. Here both coding intervals and strands are supplied; no gene or splice-site discovery is required. Apply the equal-length DNA replacement and translate each annotated window before and after it. For these windows, use internal codon meanings throughout and retain stops as * rather than truncating: the goal is to expose every codon-level consequence. Role in related tasksWhen two annotated coding windows overlap, a DNA edit can change both products. The overlapping-product audit uses this comparison to check the intended edit and the product that must remain fixed. The windows are supplied; discovering overlapping genes is a different problem. Task OutlineInputs. Procedure. Translate window A (7–12) as AI and window B (6–11) as SN using internal-codon meanings. C8T changes A’s GCA to GTA but changes B’s AGC to synonymous AGT; report both before/after products. Final answer: [
{
"frame": "A",
"original_peptide": "AI",
"edited_peptide": "VI",
"changed": true
},
{
"frame": "B",
"original_peptide": "SN",
"edited_peptide": "SN",
"changed": false
}
]Checking the answer. All four peptide strings and the changed/unchanged flags must agree with the annotated windows and replacement. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus These are deliberately annotated overlapping test windows on native trpL, not a claim that the second frame is a natural gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus These are deliberately annotated overlapping test windows on native trpL, not a claim that the second frame is a natural gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"frame": <"A" or "B">,
"original_peptide": <amino-acid string, retaining stops as *>,
"edited_peptide": <amino-acid string, retaining stops as *>,
"changed": <boolean>
}
]Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "overlap.compare_products",
"output_format": "json",
"scorer": "exact_match",
"family": "overlap",
"domain": "multi",
"objective": "none",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
} | ||
Change one frame, preserve the otheroverlap.constrained_edit | Change DNA so one annotated coding window encodes a requested peptide while the overlapping window’s peptide stays unchanged. | |
Change one frame, preserve the otherThe two coding windows and their strands are supplied, together with an exact target peptide for the first and a list of DNA positions allowed to change. The original second-window peptide is the product that must be preserved. Search substitutions at those shared DNA positions and evaluate both translations after every candidate choice. A synonymous change in one window may alter the other, so separately choosing codons for the two peptides is insufficient. Use the same internal-translation convention as the overlap-comparison task. Practical contextThe overlap-comparison task describes a real shared-exon example. When one DNA segment encodes two products, a mutation intended for one can recode the other. This task searches exact peptide-preserving constraints, and the verification composition reports both products so the intended protection can be checked. Method reference: NCBI CDKN2A annotation. Task OutlineInputs. Procedure. Test the four possible bases at editable position 8. C8T yields VI in frame A and keeps SN in frame B. Every other DNA position remains fixed. Final answer: ATGAAAGTAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCTGA Checking the answer. One final DNA sequence must satisfy both peptide requirements and the edit permissions. Return IMPOSSIBLE when the coupled constraints have no solution. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus The two overlapping test windows are supplied annotations, not two natural genes. C8T changes frame A Ala→Val while preserving the overlapping frame B Ser codon AGC→AGT. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus The two overlapping test windows are supplied annotations, not two natural genes. C8T changes frame A Ala→Val while preserving the overlapping frame B Ser codon AGC→AGT. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Formal fields and scoring
Prompt templates start from a CDS and include any required transcription or translation. Literal task fields{
"task_type": "overlap.constrained_edit",
"output_format": "scalar",
"scorer": "exact_match",
"family": "overlap",
"domain": "multi",
"objective": "none",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
} | ||
Composition tasks (19)
Each composition task lists the tasks it combines and explains how one task’s output is used by another. Some run tasks in sequence, some use the same result for several calculations, and others require one sequence to satisfy several conditions at once.
Composition types
Pipeline: CDS → protein → peptide intervals → DNA intervals.
Branch: one protein → mass, charge, and composition.
Joint: one CDS must preserve protein, remove sites, and meet GC bounds simultaneously.
For a joint design, completing one rewrite and then another can undo earlier constraints. Every condition must be checked on the same final sequence.
| Task | Description | Expand details |
|---|---|---|
From peptide motif to encoding DNApipeline.motif_to_dna | Find a supplied pattern in the CDS’s encoded protein, then report the DNA intervals encoding those protein matches. | |
From peptide motif to encoding DNAThe input is a CDS plus an amino-acid pattern. First translate the CDS and find all matching residue intervals. For each match, map that interval back to the original DNA using the known reading frame. This asks the model to search at one biological level and report locations at another, rather than searching for the protein letters in DNA. Practical contextThis prepares a protein-level feature for DNA engineering: locate the supplied motif and identify the codons that encode it. Those coordinates can feed permitted motif removal or a planned substitution, without asking the model to infer which sequence features are functional. Component tasksTranslate DNA to protein
cds.translateFind a supplied peptide patternprotein.motif_positionsMap residues back to DNAcoords.aa_to_ntTask OutlineInputs. Procedure. Translate native trpL and find WWRT matching WWX[ST] at residues 10–13. Convert the interval to original DNA using 3×10−2 = 28 and 3×13 = 39. Final answer: [
{
"aa_interval": [10, 13],
"nt_interval": [28, 39]
}
]Checking the answer. Every protein match and its corresponding DNA interval must be correct; overlapping matches remain separate results. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"aa_interval": [<first residue>, <last residue>],
"nt_interval": [<first base>, <last base>]
}
]Steps and final outputTranslate the CDS, then find the motif in that protein. Convert each matching residue interval into nucleotide coordinates using the original CDS. Output: JSON array of records in the specified order Literal task fields{
"composition_type": "pipeline.motif_to_dna",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Annotated CDS initiation, NCBI genetic code 11: internal DNA codons | ||
From CDS to defined protein measurementspipeline.protein_properties | Translate one CDS and calculate a fixed set of measurements from that same encoded protein. | |
From CDS to defined protein measurementsThe question supplies a CDS, a pH, and pKa values. Translate once, then use the same product for residue counts, mass, mean hydropathy, charge at the supplied pH, and pI. This is a branching composition: no measurement changes the sequence passed to another measurement. Practical contextThis resembles a construct-characterization report: theoretical mass supports product identification, and charge or pI supports purification planning. Hydropathy and composition add descriptive context. The measurements answer separate questions; combining them does not create a general predictor of protein expression or function. Method references: ExPASy ProtParam documentation, Cytiva ion-exchanger selection guide. Component tasksTranslate DNA to protein
cds.translateCount amino acidsprotein.residue_countsCalculate peptide massprotein.monoisotopic_massCalculate mean hydropathyprotein.mean_hydropathyCalculate model charge at a pHprotein.charge_at_phCalculate the isoelectric point (pI)protein.isoelectric_pointTask OutlineInputs. Procedure. Translate once to MKAIFVLKGWWRTS. Use that same sequence for counts, residue-mass sum plus one water, mean hydropathy, charge at pH 7, and the pH where that charge becomes zero. Final answer: {
"residue_counts": {
"M": 1,
"K": 2,
"A": 1,
"I": 1,
"F": 1,
"V": 1,
"L": 1,
"G": 1,
"W": 2,
"R": 1,
"T": 1,
"S": 1
},
"mass_da": 1721.944,
"mean_hydropathy": 0.2143,
"charge": 2.9095,
"pi": 11.67
}Checking the answer. Each named measurement is checked under its own stated convention and numerical precision. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"residue_counts": {"<one-letter amino-acid symbol>": <positive integer count>},
"mass_da": <number>,
"mean_hydropathy": <number>,
"charge": <number>,
"pi": <number>
}Steps and final outputTranslate the CDS once and use that same protein for all five measurements. Both prompt variants supply the pH and any custom pKa values. Return all five named measurements. Output: JSON object with exactly residue_counts, mass_da, mean_hydropathy, charge, pi Literal task fields{
"composition_type": "pipeline.protein_properties",
"output_format": "json",
"scorer": "exact_match",
"mode": "branch",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Annotated CDS initiation, NCBI genetic code 11: internal DNA codons, Monoisotopic isotope masses, Monoisotopic residue masses, Kyte–Doolittle hydropathy scores, Ionization and net charge | ||
From CDS panel to a diagnostic peptidepipeline.diagnostic_digest | From target and comparison CDSs, identify a protein-digest peptide that distinguishes the target from the supplied panel. | |
From CDS panel to a diagnostic peptideStart with one target CDS encoding the protein you want to identify, and comparison CDSs encoding the other proteins you want to distinguish it from. The comparison set is called the background in the input fields. Translate every CDS and digest every protein using the same trypsin rule. Discard target peptides also found in any comparison digest, then apply the peptide-length limits. Choose the shortest remaining peptide, breaking ties alphabetically; return NONE if none remains. The result distinguishes the target only from the supplied comparison set. Practical contextThis is a first stage in choosing a proteomics readout that distinguishes related proteins. Deriving the peptide from each actual CDS checks that its uniqueness survives translation and digestion. Experimental assay development must then establish that the candidate peptide is observable and measurable. Method reference: ExPASy PeptideMass documentation. Component tasksTranslate DNA to protein
cds.translateDigest with trypsin rulesprotein.trypsin_digestSelect a distinguishing peptideprotein.diagnostic_peptideTask OutlineInputs. Procedure. Translate and digest both the native target and I4V comparison. Their shared fragments are MK, GWWR, and TS; AIFVLK appears only in the target digest and meets the length bounds. Final answer: AIFVLK Checking the answer. The final peptide must be eligible and correctly selected from the actual translated-and-digested products, or NONE must be justified by the absence of eligible peptides. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL is the target. The comparison is a designed I4V variant (codon 4 ATT→GTT), not a second natural accession. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL is the target. The comparison is a designed I4V variant (codon 4 ATT→GTT), not a second natural accession. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionFrom eligible target-only peptide sequences, choose the shortest, then the ASCII-lexicographically smallest sequence. Multiple copies of one sequence do not create separate choices. If no target-only peptide meets the length limits, return: NONE Steps and final outputTranslate and digest the target CDS and each comparison CDS (the background set). Compare the target peptides with all comparison peptides. Select the shortest target-only peptide, breaking ties alphabetically, or return NONE if no peptide meets the length limits. Output: one peptide or NONE Literal task fields{
"composition_type": "pipeline.diagnostic_digest",
"output_format": "scalar",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "From eligible target-only peptide sequences, choose the shortest, then the ASCII-lexicographically smallest sequence. Multiple copies of one sequence do not create separate choices."
}Reference material. Annotated CDS initiation, NCBI genetic code 11: internal DNA codons, Trypsin cleavage specificity | ||
From DNA edits to changed peptide readoutspipeline.variant_peptides | Apply DNA edits and determine which tryptic peptide sequences are lost or gained relative to the original CDS. | |
From DNA edits to changed peptide readoutsKeep two branches: the original CDS and a copy with the supplied DNA edits. Translate and digest both. Compare their peptide-sequence sets to identify readouts removed or introduced by the edit. An edit can change not only a peptide’s letters but also a cleavage site and therefore the fragment boundaries. Practical contextAn engineered DNA change can alter a peptide sequence or create or remove a cleavage boundary. Following both branches identifies candidate readouts for checking whether the edited protein product was made, before developing a mass-spectrometry assay around those products. Method reference: ExPASy PeptideMass documentation. Component tasksApply a DNA edit script
variant.applyTranslate DNA to proteincds.translateDigest with trypsin rulesprotein.trypsin_digestTask OutlineInputs. Procedure. The K2A DNA change removes the first trypsin cut. Original MK and AIFVLK merge to MAAIFVLK; compare peptide sequence sets to report lost and gained readouts. Final answer: {
"lost": ["AIFVLK", "MK"],
"gained": ["MAAIFVLK"]
}Checking the answer. Both lost and gained sets must match the two digests. This composition ignores peptide multiplicity when taking those set differences. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"lost": [<amino-acid string>],
"gained": [<amino-acid string>]
}Steps and final outputTranslate and digest both the original and edited CDS. Report lost peptides as sequences present only in the original digest, and gained peptides as sequences present only in the edited digest. Count repeated copies only once for these two comparisons. Output: JSON object with exactly lost, gained Literal task fields{
"composition_type": "pipeline.variant_peptides",
"output_format": "json",
"scorer": "exact_match",
"mode": "branch",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Initiation after DNA editing, NCBI genetic code 11: internal DNA codons, Trypsin cleavage specificity | ||
From specified RNA edits to proteinpipeline.rna_edit_translation | Transcribe a CDS, apply supplied RNA edits, and translate the edited RNA to obtain the final protein. | |
From specified RNA edits to proteinThe CDS gives the initial coding RNA, and the question states the exact RNA edits. Apply those edits before translating. The original DNA is retained as the source, but it must not be used in place of the edited RNA at the final step. This tests the consequence of a change introduced specifically at the RNA stage. Practical contextApoB provides a direct biological counterpart: APOBEC1-mediated C-to-U editing turns a CAA glutamine codon into a UAA stop, producing a shorter protein. The worked example uses that same codon change on a small illustrative CDS. The edit is supplied; predicting the enzyme’s site selection is outside the task. Method references: ApoB RNA editing: CAA becomes a stop codon, The apoB-editing catalytic subunit is a cytidine deaminase. Component tasksMake the coding RNA
dna.transcribeApply specified RNA editsrna.apply_editsTranslate coding RNArna.translateTask OutlineInputs. Procedure. Transcribe the R12Q substrate, then change RNA C34 to U. CAA at codon 12 becomes UAA, so translation stops after MKAIFVLKGWW and excludes all downstream codons. Final answer: MKAIFVLKGWW Checking the answer. The final amino-acid sequence must be the translation of the edited RNA under the specified start and stop conventions. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with R12Q (CGC→CAA), followed by a supplied C34→U RNA edit converting CAA to UAA. It illustrates a premature stop; no native trpL editing event is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with R12Q (CGC→CAA), followed by a supplied C34→U RNA edit converting CAA to UAA. It illustrates a premature stop; no native trpL editing event is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
Steps and final outputTranscribe the CDS, apply the supplied RNA edits, then translate the edited RNA. Start at the original reading origin and stop at the first in-frame stop codon. Output: post-edit protein string Literal task fields{
"composition_type": "pipeline.rna_edit_translation",
"output_format": "scalar",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Coding DNA to RNA, Initiation of coding RNA, NCBI genetic code 11: internal RNA codons | ||
From specified RNA edits to RNA fragmentspipeline.rna_edit_digest | Apply specified edits to a CDS-derived RNA and determine the RNA fragments produced afterward by RNase T1. | |
From specified RNA edits to RNA fragmentsTranscribe the CDS, apply the supplied RNA edits, then use the sequence-only RNase T1 rule on that edited RNA. Editing can change a fragment’s letters even when the cuts stay fixed; literal substitutions that add or remove G can also change cut positions. This composition uses explicit A/C/G/U letters. Treating inosine as G for translation does not establish RNase T1 cleavage chemistry at inosine. Practical contextA supplied RNA edit changes the sequence fingerprint expected from a real RNase T1 digest. The example uses C→U, as in apoB editing: it changes letters within a fragment without changing the G-dependent cuts. This is sequence interpretation for RNA characterization, with mass spectrometry providing a possible downstream readout. Method references: RNase T1: enzyme specificity and applications, RNA and mRNA sequence mapping by mass spectrometry. Component tasksMake the coding RNA
dna.transcribeApply specified RNA editsrna.apply_editsDigest coding RNA with RNase T1 rulesrna.t1_digestTask OutlineInputs. Procedure. Apply the same C34→U edit to the complete RNA, then cut after every G under the RNase T1 rule. Translation stopping at UAA does not truncate the RNA used for this digest. Final answer: [
{
"start": 1,
"end": 3,
"fragment": "AUG"
},
{
"start": 4,
"end": 7,
"fragment": "AAAG"
},
{
"start": 8,
"end": 16,
"fragment": "CAAUUUUCG"
},
{
"start": 17,
"end": 21,
"fragment": "UACUG"
},
{
"start": 22,
"end": 25,
"fragment": "AAAG"
},
{
"start": 26,
"end": 26,
"fragment": "G"
},
{
"start": 27,
"end": 29,
"fragment": "UUG"
},
{
"start": 30,
"end": 30,
"fragment": "G"
},
{
"start": 31,
"end": 32,
"fragment": "UG"
},
{
"start": 33,
"end": 33,
"fragment": "G"
},
{
"start": 34,
"end": 44,
"fragment": "UAAACUUCCUG"
},
{
"start": 45,
"end": 45,
"fragment": "A"
}
]Checking the answer. Fragment sequences and intervals must describe the edited RNA’s digest, not the original RNA’s digest. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with R12Q (CGC→CAA), followed by a supplied C34→U RNA edit converting CAA to UAA. It illustrates a premature stop; no native trpL editing event is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Native trpL with R12Q (CGC→CAA), followed by a supplied C34→U RNA edit converting CAA to UAA. It illustrates a premature stop; no native trpL editing event is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"start": <positive integer>,
"end": <positive integer>,
"fragment": <RNA string>
}
]Steps and final outputDigest the edited RNA with the RNase T1 rule. This question treats every G as accessible (accessibility=all, pairs=[]); it does not reuse a pairing map from before the edits. Output: JSON array of records in the specified order Literal task fields{
"composition_type": "pipeline.rna_edit_digest",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Coding DNA to RNA, RNase T1 cleavage specificity | ||
From a pairing annotation to eligible cutspipeline.structure_gated_digest | Use a supplied RNA-structure annotation to decide which RNase T1 cuts are allowed in coding RNA. | |
From a pairing annotation to eligible cutsThe question supplies a CDS and a dot-bracket annotation of its coding RNA. Convert the annotation into paired positions, then permit cleavage only at G bases marked unpaired. The structure stays fixed for the calculation; the model is not asked to refold fragments after cutting. Exercise scopeRNase T1 preferentially cleaves single-stranded G sites; RNA protection assays exploit the difference between exposed and protected RNA. That gives the composition a biochemical basis. Its fixed pairing map and binary cut/no-cut mask simplify actual accessibility and reaction kinetics rather than predicting an experimental digestion pattern. Method reference: RNase T1: enzyme specificity and applications. Component tasksMake the coding RNA
dna.transcribeDecode a pairing maprna.dotbracket_to_pairsDigest coding RNA with RNase T1 rulesrna.t1_digestTask OutlineInputs. Procedure. Decode the supplied annotation and mark every paired nucleotide. Cut after G only if that G is unpaired; G25 and G26 are protected, so their neighboring digest intervals merge. Final answer: [
{
"start": 1,
"end": 3,
"fragment": "AUG"
},
{
"start": 4,
"end": 7,
"fragment": "AAAG"
},
{
"start": 8,
"end": 16,
"fragment": "CAAUUUUCG"
},
{
"start": 17,
"end": 21,
"fragment": "UACUG"
},
{
"start": 22,
"end": 29,
"fragment": "AAAGGUUG"
},
{
"start": 30,
"end": 30,
"fragment": "G"
},
{
"start": 31,
"end": 32,
"fragment": "UG"
},
{
"start": 33,
"end": 33,
"fragment": "G"
},
{
"start": 34,
"end": 35,
"fragment": "CG"
},
{
"start": 36,
"end": 44,
"fragment": "CACUUCCUG"
},
{
"start": 45,
"end": 45,
"fragment": "A"
}
]Checking the answer. Every returned cut must satisfy both the sequence rule and the supplied structural eligibility rule. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus The fixed pairing annotation is supplied for the exercise, not inferred from trpL biology. It protects the paired G bases at positions 25 and 26 from the stated RNase T1 rule. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus The fixed pairing annotation is supplied for the exercise, not inferred from trpL biology. It protects the paired G bases at positions 25 and 26 from the stated RNase T1 rule. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. [
{
"start": <positive integer>,
"end": <positive integer>,
"fragment": <RNA string>
}
]Steps and final outputTranscribe the CDS and convert the supplied dot-bracket notation into paired positions. Use both to digest the RNA with accessibility=unpaired_only. Keep the supplied pairing map fixed during cleavage. Output: JSON array of records in the specified order Literal task fields{
"composition_type": "pipeline.structure_gated_digest",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Coding DNA to RNA, Dot-bracket notation, RNase T1 cleavage specificity | ||
Remove cloning sites while controlling GCjoint.clone_ready_cds | Find one synonymous CDS that removes unwanted DNA sites and satisfies every supplied local GC requirement. | |
Remove cloning sites while controlling GCThe input supplies forbidden patterns, a strand-search rule, and local GC limits. Both requirements apply to the same final CDS. Removing a site and then fixing GC can recreate the site, so a sequence is accepted only after all checks pass together. The encoded protein and fixed terminal codons must also be preserved. Practical contextThis combines two ordinary construct-design requirements: remove internal sites that would interfere with an assembly method and avoid unsuitable local GC while keeping the protein fixed. Practical constraint-based tools handle this kind of simultaneous repair, because fixing one feature can create another violation. Method references: GoldenMutagenesis domestication, DNA Chisel examples. Component tasksRemove specified DNA motifs
design.remove_dna_motifsControl local GC by recodingdesign.gc_windowsCompare encoded proteinscds.protein_equivalenceTask OutlineInputs. Procedure. For each synonymous cloning-substrate encoding, jointly require no GAATTC on either strand and compliant GC fractions in every nine-base window. Choose the first complete DNA satisfying both conditions. Final answer: ATGAAAGAGTTCTTCGTACTATGA Checking the answer. Any one candidate satisfying all final requirements is accepted. If none exists, the instance needs a certified IMPOSSIBLE answer. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3E and I4F substitutions (GCA→GAA, ATT→TTC), creating the real EcoRI recognition sequence GAATTC at bases 7–12. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3E and I4F substitutions (GCA→GAA, ATT→TTC), creating the real EcoRI recognition sequence GAATTC at bases 7–12. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Steps and final outputFind one CDS that removes the forbidden motifs and meets every GC-window bound. Check both conditions on the final sequence, verify that it encodes the original protein, and keep the first and last codons unchanged. A later rewrite must not undo an earlier requirement. Output: canonical DNA string, or IMPOSSIBLE Literal task fields{
"composition_type": "joint.clone_ready_cds",
"output_format": "scalar",
"scorer": "exact_match",
"mode": "joint",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
}Reference material. Synonymous codons, NCBI genetic code 11: internal DNA codons, IUPAC DNA base sets, DNA reverse complement, GC fraction | ||
Repair RNA pairs and verify the proteinpipeline.repair_and_verify | Repair specified coding-RNA pairs through synonymous DNA edits, then verify both pairing and protein preservation. | |
Repair RNA pairs and verify the proteinThe question gives the original CDS, intended RNA pairs, and positions allowed to change. Propose a synonymous repair, transcribe that candidate, and check its pairs. Independently compare the candidate’s protein with the original protein. This makes both conditions explicit rather than treating one as a consequence of the other. Practical contextThe rpsT compensatory-mutation study supplies a concrete precedent for repairing proposed coding-RNA contacts through synonymous changes. This composition verifies that the designed sequence restores the specified pairs and retains the protein. A resulting sequence is a candidate experimental control; the pair check alone cannot establish its fitness effect. Method reference: Synonymous mutations and restoration of mRNA base pairing. Component tasksRepair pairing synonymously
design.pairing_repairMake the coding RNAdna.transcribeCheck specified RNA pairsrna.pair_compatibilityCompare encoded proteinscds.protein_equivalenceTask OutlineInputs. Procedure. Repair the supplied G3–A9 contact using only DNA base 9, then translate that same final CDS. GCC supplies the required C9 while preserving the original MKAIFVL protein. Final answer: ATGAAAGCCATTTTCGTACTGTGA Checking the answer. One final CDS must pass the RNA-pair check, protein-equivalence check, and edit permissions. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The supplied pair (3,9) is initially G–A; the only permitted DNA position is the third base of Ala codon 3. The map is an illustrative repair target. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The supplied pair (3,9) is initially G–A; the only permitted DNA position is the third base of Ala codon 3. The map is an illustrative repair target. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. If no valid result exists, return: IMPOSSIBLE Steps and final outputTranscribe the repaired CDS and check every supplied RNA pair. Translate the repaired and original CDSs to verify that they encode the same protein. Both checks must pass for the same final DNA sequence. Output: canonical DNA string, or IMPOSSIBLE Literal task fields{
"composition_type": "pipeline.repair_and_verify",
"output_format": "scalar",
"scorer": "exact_match",
"mode": "branch",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
}Reference material. Synonymous codons, NCBI genetic code 11: internal DNA codons, Coding DNA to RNA, Canonical RNA base pairs | ||
Balance an RNA structural constraint and codon preferencejoint.structure_and_codons | Within a changed-base budget, preserve the protein and meet an RNA pair-score threshold while maximizing codon preference. | |
Balance an RNA structural constraint and codon preferenceThe input gives allowed DNA-change counts, a fixed RNA pair map, pair scores, a minimum total pair score, and codon-preference weights. First define feasible synonymous candidates: each must satisfy the edit range and structural threshold. Among those candidates, maximize codon adaptation index. The structure score is a pass/fail constraint here, not a second objective to maximize. Exercise scopeThe composition models the structure of a multi-objective design problem, but its supplied pair-score threshold is artificial. LinearDesign is a practical counterpart that combines codon adaptation with a thermodynamic RNA-folding objective. The benchmark tests constraint coordination without claiming to reproduce that stability model. Method reference: LinearDesign. Component tasksRewrite with a specified number of DNA changes
design.synonymous_distanceMake the coding RNAdna.transcribeScore a specified RNA structurerna.structure_scoreCalculate codon adaptation indexstats.caiTask OutlineInputs. Procedure. Keep candidates with exactly two changed bases and a canonical pair between RNA positions 9 and 18 scoring at least two. Maximize the product of internal codon weights among those candidates, then apply the DNA tie-break. Final answer: ATGAAAGCCATTTTCGTGCTGTGA Checking the answer. The accepted candidate must satisfy every feasibility condition and attain the best codon score among feasible candidates. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Pair map and codon weights are supplied illustrative inputs. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Pair map and codon weights are supplied illustrative inputs. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionAfter achieving the stated optimum, break ties by the lexicographically smallest full DNA string, with A<C<G<T. Compare objective values before rounding. If no valid result exists, return: IMPOSSIBLE Steps and final outputKeep the protein unchanged and obey edit_bounds. The candidate’s coding RNA must satisfy every supplied pair and reach min_pair_score under wc_additive_v1. Among candidates meeting those conditions, maximize CAI using the supplied codon weights. Check all conditions on that same sequence. Output: canonical DNA string, or IMPOSSIBLE Literal task fields{
"composition_type": "joint.structure_and_codons",
"output_format": "scalar",
"scorer": "exact_match",
"mode": "joint",
"selection_rule": "After achieving the stated optimum, break ties by the lexicographically smallest full DNA string, with A<C<G<T. Compare objective values before rounding."
}Reference material. Synonymous codons, NCBI genetic code 11: internal DNA codons, Coding DNA to RNA, Canonical RNA base pairs, Codon adaptation index | ||
Choose an RNA probe and a matched escape controlpipeline.target_and_escape | Choose a target-specific RNA probe, then make a synonymous version of the target that no longer closely matches that same probe. | |
Choose an RNA probe and a matched escape controlUse the target and comparison CDSs to select the required probe by the probe-selection task’s rules. Keep that selected probe fixed while redesigning the target CDS as an escape control. The redesigned target must preserve its protein and meet the supplied mismatch minimum at every RNA window. The comparisons stay unchanged. Practical contextThis provides a sequence-level analogue of an RNAi target and rescue control: the original RNA matches the reagent, while a synonymous construct preserves the protein and disrupts that match. Actual knockdown and rescue depend on reagent activity; a mismatch threshold is only the design screen. Method reference: RNAi-resistant rescue in a B-cyclin study. Component tasksMake the coding RNA
dna.transcribeSelect a CDS-specific RNA probeassay.select_rna_probeMatch an RNA guiderna.guide_hitsCreate a guide-escape controldesign.guide_escapeTask OutlineInputs. Procedure. First select the same target-specific 12-base probe as the probe-selection task. Keep it fixed, rewrite only permitted synonymous positions, and require every target window to have at least one mismatch to that probe’s reverse complement. Final answer: {
"status": "ok",
"probe": "AAAAUUGCUUUC",
"escape_cds": "ATGAAAGCAATATTCGTACTATGA"
}Checking the answer. Check probe selection and escape design separately, then verify that the reported probe is the one used to construct the control. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Comparison is a designed I4V minigene variant (ATT→GTT). Probes and escape changes are computed design exercises, not validated reagents. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Comparison is a designed I4V minigene variant (ATT→GTT). Probes and escape changes are computed design exercises, not validated reagents. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
SelectionFirst select the ASCII-lexicographically smallest probe meeting the original target/background requirements (A<C<G<U). Keep it fixed, then choose the lexicographically smallest feasible escape DNA (A<C<G<T). If that selected probe has no feasible escape, return impossible; do not try a later probe. Output structureUse exactly this structure. {
"status": "ok",
"probe": <RNA string>,
"escape_cds": <DNA string>
}
If no valid result exists, return: {
"status": "impossible",
"probe": null,
"escape_cds": null
}Steps and final outputTranscribe the target and background CDSs, then select a 5′→3′ RNA probe. Use that same probe sequence for the guide-matching and escape-redesign tasks. Every window in the redesigned target must have at least escape_mismatches mismatches to the probe. Keep the background sequences unchanged. Output: JSON object with exactly status, probe, escape_cds Literal task fields{
"composition_type": "pipeline.target_and_escape",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "First select the ASCII-lexicographically smallest probe meeting the original target/background requirements (A<C<G<U). Keep it fixed, then choose the lexicographically smallest feasible escape DNA (A<C<G<T). If that selected probe has no feasible escape, return impossible; do not try a later probe."
}Reference material. Synonymous codons, NCBI genetic code 11: internal DNA codons, Coding DNA to RNA, RNA reverse complement | ||
Encode a protein change and remove cloning sitesjoint.protein_edit_and_cloning | Introduce one requested amino-acid change and remove forbidden DNA sites with the fewest total base substitutions. | |
Encode a protein change and remove cloning sitesThe requested mutation defines the target protein: one residue changes and all others remain original. Synonymous edits elsewhere are allowed to remove unwanted DNA sites. Search those choices together and minimize the total number of changed DNA bases, while preserving the fixed first and terminal stop codons. This differs from freezing the locally cheapest codon change before attempting cleanup. Practical contextThis turns a requested amino-acid change into a construct compatible with a chosen assembly method. The final translation checks the desired mutation, while motif checks ensure that unwanted restriction sites were not retained or created by the edits. Method references: GoldenMutagenesis domestication, Site-directed mutagenesis protocol. Component tasksEncode a requested amino-acid substitution
construct.minimal_aa_editRemove specified DNA motifsdesign.remove_dna_motifsTranslate DNA to proteincds.translateTask OutlineInputs. Procedure. Replace Asp3 with Glu in the cloning substrate. GAA would create GAATTC with the next Phe codon; GAG makes the same requested Glu substitution without that site and with the minimum number of base changes. Final answer: ATGAAAGAGTTCTTCGTACTGTGA Checking the answer. The final CDS must encode exactly the requested mutant protein, contain no forbidden sites, and minimize total changes with the stated tie-break. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The A3E/I4F cloning substrate instead starts with Asp at position 3 (GAT). Its requested D3E edit must avoid introducing GAATTC. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The A3E/I4F cloning substrate instead starts with Asp at position 3 (GAT). Its requested D3E edit must avoid introducing GAATTC. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · scalar
SelectionMinimize the total number of changed nucleotides permitted by this task; among equally minimal candidates, return the lexicographically smallest full DNA string (A<C<G<T). If no valid result exists, return: IMPOSSIBLE Steps and final outputIntroduce the requested amino-acid substitution and use synonymous changes elsewhere to remove forbidden sites. Minimize the total number of nucleotide substitutions while meeting both requirements; break ties by DNA lexicographic order. The fewest edits needed for the amino-acid substitution alone provide a comparison, but those particular edits need not be retained in the final design. Output: canonical DNA string, or IMPOSSIBLE Literal task fields{
"composition_type": "joint.protein_edit_and_cloning",
"output_format": "scalar",
"scorer": "exact_match",
"mode": "joint",
"selection_rule": "Minimize the total number of changed nucleotides permitted by this task; among equally minimal candidates, return the lexicographically smallest full DNA string (A<C<G<T)."
}Reference material. Synonymous codons, NCBI genetic code 11: internal DNA codons, IUPAC DNA base sets, DNA reverse complement | ||
Build a tagged construct, cleave it, measure productspipeline.tag_cleave_mass | Assemble a tagged CDS, translate it, simulate TEV cleavage, and calculate the mass of each resulting fragment. | |
Build a tagged construct, cleave it, measure productsThe input supplies tag and linker DNA plus its placement. Assemble the construct by the stated convention, translate the assembled DNA, and cut the product at the benchmark TEV sites. Then calculate each fragment’s mass separately. This tracks both module assembly and the residues left on each side of cleavage. Practical contextThis follows an affinity-tagged construct through tag removal to expected product identity. Keeping track of the exact cleavage scar matters because the purified target’s sequence and theoretical mass can differ from both the original untagged protein and the full fusion. Method references: Removal of affinity tags with TEV protease, ExPASy PeptideMass documentation. Component tasksBuild a tagged protein CDS
construct.tag_fusionTranslate DNA to proteincds.translateDerive TEV-cleaved productsconstruct.tev_productsCalculate peptide massprotein.monoisotopic_massTask OutlineInputs. Procedure. Build the same His6–TEV/GGS fusion as tag_fusion, translate it, and cut ENLYFQ|G. Sum each fragment’s residue masses plus its own water molecule, rounding each fragment mass once. Final answer: {
"cds": "ATGCATCATCATCATCATCATGAAAATCTGTATTTTCAGGGTGGTTCTAAAGCAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCTGA",
"fragments": [
{
"peptide": "MHHHHHHENLYFQ",
"mass_da": 1765.7644
},
{
"peptide": "GGSKAIFVLKGWWRTS",
"mass_da": 1791.9784
}
]
}Checking the answer. Check the constructed DNA, all cleavage-product sequences, and each fragment’s calculated mass. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus The supplied modules encode a His6 tag followed by a TEV site (HHHHHHENLYFQ) and a GGS linker. These are designed additions to native trpL. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus The supplied modules encode a His6 tag followed by a TEV site (HHHHHHENLYFQ) and a GGS linker. These are designed additions to native trpL. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"cds": <DNA string>,
"fragments": [
{
"peptide": <amino-acid string>,
"mass_da": <number>
}
]
}Steps and final outputConstruct the tagged CDS, translate it, and apply the TEV cleavage rule. Calculate the monoisotopic mass of each final fragment, adding one H2O per fragment. The supplied tag and linker must encode the intended TEV site; residues remaining on each side follow the ENLYFQ|G cut. Output: JSON object with exactly cds, fragments Literal task fields{
"composition_type": "pipeline.tag_cleave_mass",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Annotated CDS initiation, NCBI genetic code 11: internal DNA codons, Monoisotopic isotope masses, Monoisotopic residue masses | ||
Design a codon library and verify its coveragepipeline.library_and_verify | Design a degenerate codon for requested amino acids, then expand it to verify coverage and absence of stops. | |
Design a codon library and verify its coverageChoose the IUPAC codon under the focused-library task’s optimization rules. Insert that notation at the selected internal CDS position, enumerate every concrete codon, and count its protein products. The final enumeration checks what the compact notation actually permits rather than relying on the intended target list. Practical contextThis connects the intent of a focused mutagenesis library to what will actually be synthesized. Enumerating the proposed degenerate codon checks target amino-acid coverage, unintended products, and stops before ordering the oligonucleotide mixture. Method reference: SwiftLib. Component tasksDesign a focused degenerate codon
library.design_codonEnumerate a degenerate codon librarylibrary.codon_productsAssess an ambiguous stopambiguity.stop_certaintyTask OutlineInputs. Procedure. Choose the optimal stop-free IUPAC triplet for A/G/V coverage, then expand that selected triplet again and count each concrete codon’s internal amino-acid product. Report the design and its complete expansion counts. Final answer: {
"status": "ok",
"codon": "GBA",
"residue_counts": {
"A": 1,
"G": 1,
"V": 1
}
}Checking the answer. The chosen codon must be optimal under the declared objective, and its reported residue multiplicities must match its full expansion. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
SelectionRequire target-residue coverage and no stops. Minimize extra amino-acid types, then the number of concrete codons, then the IUPAC triplet in ASCII order A<B<C<D<G<H<K<M<N<R<S<T<V<W<Y. Compare the symbols themselves, not their expanded nucleotide sets. Output structureUse exactly this structure. {
"status": "ok",
"codon": <IUPAC DNA triplet>,
"residue_counts": {"<one-letter amino-acid symbol>": <positive integer count>}
}
If no valid result exists, return: {
"status": "impossible",
"codon": null,
"residue_counts": null
}Steps and final outputReplace the selected codon with the chosen IUPAC triplet. Expand that same codon to enumerate its amino-acid products and check whether it can encode a stop. The products must cover target_residues, and none of the codon expansions may be a stop (stop status=never). Output: JSON object with exactly status, codon, residue_counts Literal task fields{
"composition_type": "pipeline.library_and_verify",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Require target-residue coverage and no stops. Minimize extra amino-acid types, then the number of concrete codons, then the IUPAC triplet in ASCII order A<B<C<D<G<H<K<M<N<R<S<T<V<W<Y. Compare the symbols themselves, not their expanded nucleotide sets."
}Reference material. IUPAC DNA base sets, NCBI genetic code 11: internal DNA codons | ||
Assemble coding modules and locate junction motifspipeline.fusion_junction | Join two CDS modules, find peptide-pattern matches in the fusion product, and map those matches to the fused DNA. | |
Assemble coding modules and locate junction motifsAssemble the modules using the supplied linker and start/stop convention, then translate the fusion. Search the whole protein, including patterns formed across a module junction. Map each result to coordinates in the new fused CDS, not to the coordinate systems of the two original inputs. Practical contextA fusion can introduce a peptide feature that neither module contains on its own. Checking across each junction and mapping a hit back to DNA supplies the information needed for a subsequent allowed repair, such as removing an unwanted protease site. Component tasksJoin coding modules
construct.join_modulesTranslate DNA to proteincds.translateFind a supplied peptide patternprotein.motif_positionsMap residues back to DNAcoords.aa_to_ntTask OutlineInputs. Procedure. Build the same full-length/GGS/minigene fusion as join_modules. SGGSK crosses from the first module’s final Ser through the linker to the second module’s Lys; locate it in the fused protein and map to fused-DNA coordinates. Final answer: {
"fused_cds": "ATGAAAGCAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCGGTGGTTCTAAAGCAATTTTCGTACTGTGA",
"matches": [
{
"aa_interval": [14, 18],
"nt_interval": [40, 54]
}
]
}Checking the answer. The fused DNA, all protein matches, and their fused-DNA intervals must be correct. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Join native full-length trpL to the explicitly truncated trpL minigene using a designed GGS linker. This is a constructed tandem fusion, not a natural gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Join native full-length trpL to the explicitly truncated trpL minigene using a designed GGS linker. This is a constructed tandem fusion, not a natural gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
Output structureUse exactly this structure. {
"fused_cds": <DNA string>,
"matches": [
{
"aa_interval": [<first residue>, <last residue>],
"nt_interval": [<first base>, <last base>]
}
]
}Steps and final outputTranslate the fused CDS and search the entire resulting protein, including motifs spanning the junction. Convert each matching peptide interval into coordinates in the fused DNA sequence. Output: JSON object with exactly fused_cds, matches Literal task fields{
"composition_type": "pipeline.fusion_junction",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Apply the stated procedure; the result is uniquely determined by the inputs."
}Reference material. Annotated CDS initiation, NCBI genetic code 11: internal DNA codons | ||
Design and verify an RNA-editing-dependent productpipeline.edit_dependent_product | Design a CDS that preserves the original protein before RNA editing and gives a specified protein after the supplied edits. | |
Design and verify an RNA-editing-dependent productFirst find a permitted synonymous encoding satisfying the editing-dependent design task. Then verify two branches from that same candidate: ordinary translation must produce the original protein, and transcription followed by the supplied RNA edits and translation must produce the target protein. Returning both proteins makes the two requirements inspectable. Exercise scopeADAR-mediated RNA recoding is the biological inspiration for the revised A→G translation example. The two branches check the unedited protein and the product implied by the supplied edit. This audits encoding logic; it does not design an ADAR recognition site, guide, or editing reaction. Method reference: Programmable editing by endogenous ADAR. Component tasksDesign an RNA-editing-dependent product
construct.edit_aware_encodingTranslate DNA to proteincds.translateMake the coding RNAdna.transcribeApply specified RNA editsrna.apply_editsTranslate coding RNArna.translateTask OutlineInputs. Procedure. Choose Ser codon AGT at position 3 while preserving MKSIFVL before editing. The supplied G substitution at RNA base 7 yields Gly codon GGU; report the final DNA and both complete protein sequences. Final answer: {
"status": "ok",
"cds": "ATGAAAAGTATTTTCGTACTGTGA",
"unedited_protein": "MKSIFVL",
"edited_protein": "MKGIFVL"
}Checking the answer. Verify the DNA permissions and both exact protein products on the same designed sequence. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3S (GCA→TCT). The supplied RNA edit sets base 7 to G; choose a synonymous Ser encoding so that this edit yields Gly. No naturally observed editing is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. The minigene has A3S (GCA→TCT). The supplied RNA edit sets base 7 to G; choose a synonymous Ser encoding so that this edit yields Gly. No naturally observed editing is claimed. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. Output structureUse exactly this structure. {
"status": "ok",
"cds": <DNA string>,
"unedited_protein": <amino-acid string>,
"edited_protein": <amino-acid string>
}
If no valid result exists, return: {
"status": "impossible",
"cds": null,
"unedited_protein": null,
"edited_protein": null
}Steps and final outputTranslate the candidate CDS unchanged and verify that it encodes the original protein. Separately, transcribe the same candidate, apply the exact supplied RNA edits, and translate the edited RNA to verify target_protein. Apply the RNA edits to RNA, using its U alphabet. Output: JSON object with exactly status, cds, unedited_protein, edited_protein Literal task fields{
"composition_type": "pipeline.edit_dependent_product",
"output_format": "json",
"scorer": "exact_match",
"mode": "branch",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
}Reference material. Synonymous codons, Coding DNA to RNA, Initiation of coding RNA, NCBI genetic code 11: internal RNA codons | ||
Edit one frame and audit both productspipeline.overlap_edit_verify | Design a change for one annotated coding window while preserving the overlapping product, then report both before-and-after peptides. | |
Edit one frame and audit both productsUse the supplied windows, strands, target peptide, and edit permissions to design DNA. Compare original and designed DNA by translating each window under the overlap task’s internal-codon convention. The explicit before/after output checks both the intended change and the product that must stay fixed. Practical contextThis is a construct audit for a known coding overlap. Reporting both original and edited products verifies that the desired peptide change was achieved without silently altering the protected product. Its scope is sequence preservation under supplied annotations, rather than functional design of new overlapping genes. Component tasksChange one frame, preserve the other
overlap.constrained_editEvaluate a change in two framesoverlap.compare_productsTask OutlineInputs. Procedure. Apply the C8T solution, then independently translate both fixed overlapping windows before and after. Frame A changes AI→VI; frame B stays SN→SN. Final answer: {
"status": "ok",
"cds": "ATGAAAGTAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCTGA",
"frames": [
{
"frame": "A",
"original_peptide": "AI",
"edited_peptide": "VI",
"changed": true
},
{
"frame": "B",
"original_peptide": "SN",
"edited_peptide": "SN",
"changed": false
}
]
}Checking the answer. Check the designed DNA, both pairs of peptide strings, and every edit restriction. Easy example · references suppliedNative CDS: E. coli K-12 MG1655 trpL, locus The two overlapping test windows are supplied annotations, not two natural genes. C8T changes frame A Ala→Val while preserving the overlapping frame B Ser codon AGC→AGT. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedNative CDS: E. coli K-12 MG1655 trpL, locus The two overlapping test windows are supplied annotations, not two natural genes. C8T changes frame A Ala→Val while preserving the overlapping frame B Ser codon AGC→AGT. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
SelectionAmong all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective. Output structureUse exactly this structure. {
"status": "ok",
"cds": <DNA string>,
"frames": [
{
"frame": <"A" or "B">,
"original_peptide": <amino-acid string, retaining stops as *>,
"edited_peptide": <amino-acid string, retaining stops as *>,
"changed": <boolean>
}
]
}
If no valid result exists, return: {
"status": "impossible",
"cds": null,
"frames": null
}Steps and final outputCompare the designed and original DNA in both annotated reading windows. For the comparison task, represent the design as an equal-length replacement of the entire original interval: [1,n,designed_dna]. Frame A must encode target_peptide_a, and frame B must remain unchanged. Retain stop symbols (*) when translating these windows. Output: JSON object with exactly status, cds, frames Literal task fields{
"composition_type": "pipeline.overlap_edit_verify",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Among all sequences satisfying every condition, return the lexicographically smallest full DNA string, comparing bases in the order A<C<G<T. This is a tie-break among feasible sequences, not a minimum-edit objective."
}Reference material. DNA reverse complement, NCBI genetic code 11: internal DNA codons | ||
Build and audit a controlled synonymous panelpipeline.controlled_panel | Generate matched synonymous CDSs with different CG targets, then report their measured RNA CG counts and DNA GC fractions. | |
Build and audit a controlled synonymous panelDesign a panel in which each member meets its assigned coding-RNA CG count and all share the requested total number of G/C bases. Transcribe and measure each actual candidate, and compare its translated protein with the original. This connects design targets to independently checkable measurements. Practical contextThis prepares and audits sequences for a controlled synonymous comparison: protein identity and total GC stay fixed while CG count varies. Such panels can support experiments measuring RNA abundance or protein output. Independent measurements of each designed sequence distinguish achieved controls from merely requested ones. Method reference: Coding-sequence determinants of expression. Component tasksBuild a controlled synonymous panel
design.variant_panelCalculate total GCstats.gc_fractionMake the coding RNAdna.transcribeCount coding-RNA patternsrna.motif_countsCompare encoded proteinscds.protein_equivalenceTask OutlineInputs. Procedure. Choose the same distinct synonymous panel as variant_panel. Recount each selected member’s overlapping RNA CG occurrences and divide its full-DNA G/C count by 24 to report the measurements. Final answer: {
"status": "ok",
"members": [
{
"cds": "ATGAAAGCAATATTTGTACTATGA",
"cg_count": 0,
"gc_fraction": 0.25
},
{
"cds": "ATGAAAGCAATATTCGTATTATGA",
"cg_count": 1,
"gc_fraction": 0.25
}
]
}Checking the answer. Every sequence must satisfy its own CG target, the shared GC requirement, protein identity, and the fixed terminal-codon rule. Easy example · references suppliedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL minigene: E. coli K-12 MG1655 trpL, locus The base minigene retains native codons 1–7 and the native terminal TGA. It is an engineered truncation, not the natural full-length gene. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
SelectionAmong complete feasible panels, choose the lexicographically smallest list of DNA strings: compare the first differing member using A<C<G<T. Resolve choices across the whole panel, including distinctness; do not choose each member independently. Output structureUse exactly this structure. {
"status": "ok",
"members": [
{
"cds": <DNA string>,
"cg_count": <nonnegative integer>,
"gc_fraction": <number>
}
]
}
If no valid result exists, return: {
"status": "impossible",
"members": null
}Steps and final outputFor each candidate CDS, measure GC content, transcribe and count CG occurrences, and verify that translation gives the original protein. Each candidate must meet its own CG target and the shared total GC count. Include occurrences spanning codon boundaries. Output: JSON object with exactly status, members Literal task fields{
"composition_type": "pipeline.controlled_panel",
"output_format": "json",
"scorer": "exact_match",
"mode": "branch",
"selection_rule": "Among complete feasible panels, choose the lexicographically smallest list of DNA strings: compare the first differing member using A<C<G<T. Resolve choices across the whole panel, including distinctness; do not choose each member independently."
}Reference material. Synonymous codons, NCBI genetic code 11: internal DNA codons, Coding DNA to RNA, GC fraction | ||
From CDS collection to a minimal measurement panelpipeline.rna_probe_panel | From a collection of CDSs, choose the smallest supplied RNA-probe set giving each coding RNA a distinct match signature. | |
From CDS collection to a minimal measurement panelTranscribe each CDS and calculate which candidate probes have exact complementary hits in each RNA. Use that match matrix to choose a minimal distinguishing panel. Report the selected probe IDs and each CDS’s binary signature in the same probe order, so the claimed discrimination can be checked directly. Practical contextThis joins sequence screening to an economical measurement plan: derive probe-hit signatures and choose the smallest set that distinguishes the supplied RNAs. It addresses which measurements would be informative under exact matching; binding strength and real assay performance belong to a subsequent probe-design stage. Method reference: NUPACK documentation. Component tasksMake the coding RNA
dna.transcribeMatch an RNA guiderna.guide_hitsDistinguish CDSs with a probe panelassay.min_probe_panelTask OutlineInputs. Procedure. Select the same minimum distinguishing probe subset as min_probe_panel. In that selected ID order, encode a 1 for an exact complementary hit and 0 otherwise for each RNA in its original input order. Final answer: {
"status": "ok",
"probe_ids": ["trpL_A3_window", "trpL_R12_window"],
"signatures": [
{
"cds_index": 1,
"bits": "11"
},
{
"cds_index": 2,
"bits": "01"
},
{
"cds_index": 3,
"bits": "10"
}
]
}Checking the answer. All signatures must match sequence-derived hits, be distinct across CDSs, and come from a minimum-size panel. Easy example · references suppliedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Panel order: native trpL, synonymous Ala3 GCA→GCC variant, synonymous Arg12 CGC→CGT variant. Candidate 12-base probes are designed reverse complements of native windows 4–15, 28–39, and 16–27. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersHard example · reference knowledge assumedEngineered trpL derivative(s): E. coli K-12 MG1655 trpL, locus Panel order: native trpL, synonymous Ala3 GCA→GCC variant, synonymous Arg12 CGC→CGT variant. Candidate 12-base probes are designed reverse complements of native windows 4–15, 28–39, and 16–27. Shared source record and original sequence. Retrieved 26 October 2026. Template · unfilled placeholdersAnswer format and selection · json
SelectionMinimize the number of selected probes, then choose the lexicographically smallest sorted list of probe IDs. Compare complete ID strings in ASCII order. Output structureUse exactly this structure. {
"status": "ok",
"probe_ids": [<probe ID string>],
"signatures": [
{
"cds_index": <positive integer>,
"bits": <string of 0 and 1>
}
]
}
If no valid result exists, return: {
"status": "impossible",
"probe_ids": null,
"signatures": null
}Steps and final outputTranscribe each CDS and check every probe against every resulting RNA using guide_hits with max_mismatches=0. Record a binary match table, then choose the smallest set of probes that gives each RNA a different match pattern. Break ties using sorted probe IDs. Output: JSON object with exactly status, probe_ids, signatures Literal task fields{
"composition_type": "pipeline.rna_probe_panel",
"output_format": "json",
"scorer": "exact_match",
"mode": "pipeline",
"selection_rule": "Minimize the number of selected probes, then choose the lexicographically smallest sorted list of probe IDs. Compare complete ID strings in ASCII order."
}Reference material. Coding DNA to RNA, RNA reverse complement | ||
Reference material
These definitions and lookup tables supply the biological information used by easy prompts. Each task links only to the entries it needs. Instance data and required benchmark conventions are given in both prompt variants.
DNA reverse complement
DNA complementary bases are A↔T and C↔G. Complement each base, then reverse the sequence to write the opposite strand 5′→3′.
Coding DNA to RNA
The supplied DNA is the coding strand, written 5′→3′. Copy its bases in the same order, replacing each T with U to obtain the coding RNA.
Codon length
A codon is a group of three consecutive nucleotides.
Residue-to-codon correspondence
Each amino-acid residue is encoded by one consecutive codon. The initiating residue is residue 1; a stop codon encodes no residue.
NCBI genetic code 11: internal DNA codons
Each internal DNA codon is an aligned group of three bases. The table gives its one-letter amino-acid assignment; STOP marks a stop signal.
TTT=F TTC=F TTA=L TTG=L TCT=S TCC=S TCA=S TCG=S TAT=Y TAC=Y TAA=STOP TAG=STOP TGT=C TGC=C TGA=STOP TGG=W CTT=L CTC=L CTA=L CTG=L CCT=P CCC=P CCA=P CCG=P CAT=H CAC=H CAA=Q CAG=Q CGT=R CGC=R CGA=R CGG=R ATT=I ATC=I ATA=I ATG=M ACT=T ACC=T ACA=T ACG=T AAT=N AAC=N AAA=K AAG=K AGT=S AGC=S AGA=R AGG=R GTT=V GTC=V GTA=V GTG=V GCT=A GCC=A GCA=A GCG=A GAT=D GAC=D GAA=E GAG=E GGT=G GGC=G GGA=G GGG=G
Annotated CDS initiation
The annotated first codon of an intact CDS encodes initiating methionine (M), even when its internal-codon assignment is different.
NCBI genetic code 11: allowed DNA starts
The allowed annotated initiation codons are TTG, CTG, ATT, ATC, ATA, ATG, and GTG.
NCBI genetic code 11: DNA stop codons
The DNA stop codons are TAA, TAG, and TGA. All other unambiguous DNA codons are sense codons.
NCBI genetic code 11: internal RNA codons
Each internal RNA codon is an aligned group of three bases. The table gives its one-letter amino-acid assignment; STOP marks a stop signal.
UUU=F UUC=F UUA=L UUG=L UCU=S UCC=S UCA=S UCG=S UAU=Y UAC=Y UAA=STOP UAG=STOP UGU=C UGC=C UGA=STOP UGG=W CUU=L CUC=L CUA=L CUG=L CCU=P CCC=P CCA=P CCG=P CAU=H CAC=H CAA=Q CAG=Q CGU=R CGC=R CGA=R CGG=R AUU=I AUC=I AUA=I AUG=M ACU=T ACC=T ACA=T ACG=T AAU=N AAC=N AAA=K AAG=K AGU=S AGC=S AGA=R AGG=R GUU=V GUC=V GUA=V GUG=V GCU=A GCC=A GCA=A GCG=A GAU=D GAC=D GAA=E GAG=E GGU=G GGC=G GGA=G GGG=G
Initiation after DNA editing
At the first DNA codon, TTG, CTG, ATT, ATC, ATA, ATG, and GTG encode initiating M under NCBI genetic code 11. If the first edited codon is not one of these initiators, use its ordinary internal assignment.
Initiation of coding RNA
At the first RNA codon, UUG, CUG, AUU, AUC, AUA, AUG, and GUG encode initiating M under NCBI genetic code 11. If that first codon is not an allowed initiator, use its ordinary internal assignment.
IUPAC DNA base sets
An IUPAC symbol permits any base in its listed set. Choices at different positions are independent.
A=A C=C G=G T=T R=AG Y=CT S=CG W=AT K=GT M=AC B=CGT D=AGT H=ACT V=ACG N=ACGT
Synonymous codons
Synonymous codons encode the same amino acid. Replacing a codon with a synonymous codon preserves that residue in the protein.
GC fraction
GC fraction is the number of G and C bases divided by the number of bases in the sequence being measured.
Codon adaptation index
For n included codons with supplied positive weights w₁,…,wₙ, CAI = (w₁ × … × wₙ)^(1/n), the geometric mean of those weights.
Canonical RNA base pairs
The canonical Watson–Crick RNA pairs are A–U, U–A, C–G, and G–C.
RNA reverse complement
RNA complementary bases are A↔U and C↔G. Complement each base, then reverse the sequence to write its complementary partner 5′→3′.
Dot-bracket notation
Matching parentheses mark paired RNA positions; a dot marks an unpaired position. Each closing parenthesis pairs with the most recent unmatched opening parenthesis.
Trypsin cleavage specificity
Trypsin cleaves after K or R, except when the next residue is P. The K or R remains on the upstream peptide.
RNase T1 cleavage specificity
RNase T1 cleaves RNA after G. That G remains on the upstream fragment.
N-glycosylation sequon
The conventional N-glycosylation sequon is N–X–S or N–X–T, where X is any amino-acid residue except P.
Monoisotopic isotope masses
Use these isotope masses in Da as exact decimal constants. For a neutral, unmodified linear peptide, sum neutral free-amino-acid molecular formulas and subtract one H2O per peptide bond. Equivalently, sum incorporated residue masses and add one H2O per complete peptide. Do not round intermediate values.
12C = 12.00000000000 1H = 1.00782503223 14N = 14.00307400443 16O = 15.99491461957 32S = 31.9720711744
Monoisotopic residue masses
Use these incorporated residue masses in Da as exact decimal constants. Each is the corresponding neutral free amino acid minus one H2O. A free linear peptide has the sum of its residue masses plus one H2O, 18.01056468403 Da. Round only the final peptide mass.
A=71.03711378515 C=103.00918495955 D=115.02694302429 E=129.04259308875 F=147.06841391407 G=57.02146372069 H=137.05891185847 I=113.08406397853 K=128.09496301519 L=113.08406397853 M=131.04048508847 N=114.04292744138 P=97.05276384961 Q=128.05857750584 R=156.10111102405 S=87.03202840472 T=101.04767846918 V=99.06841391407 W=186.07931295073 Y=163.06332853364
Source: NIST isotope masses, snapshot accessed 2 November 2026. The incorporated residue masses are derived from the neutral free-amino-acid molecular formulas minus H2O, using the listed central isotope values without rounding. Measurement uncertainties are not propagated; the displayed decimal values are exact benchmark constants. Source and retrieval notes are documentation and are not included in model prompts.
Kyte–Doolittle hydropathy scores
Use these Kyte–Doolittle residue scores. Whole-protein mean hydropathy is their arithmetic mean, counting every residue occurrence.
A=1.8 R=-4.5 N=-3.5 D=-3.5 C=2.5 Q=-3.5 E=-3.5 G=-0.4 H=-3.2 I=4.5 L=3.8 K=-3.9 M=1.9 F=2.8 P=-1.6 S=-0.8 T=-0.7 W=-0.9 Y=-1.3 V=4.2
Ionization and net charge
A basic site contributes +1/(1+10^(pH−pKa)); an acidic site contributes −1/(1+10^(pKa−pH)).
Basic sites: the N terminus and K, R, H side chains. Acidic sites: the C terminus and D, E, C, Y side chains. Count each terminus once and each listed side chain once per residue occurrence; sum their contributions.
Sources and practical precedents
- NCBI genetic code 11 — Codon meanings and annotated initiators.
- INSDC feature-table specification — CDS annotations and nucleotide ambiguity conventions.
- ExPASy PeptideCutter — Protease specificity models and their experimental limits.
- DNA Chisel examples — Translation-preserving motif removal, local GC constraints, and codon optimization.
- DNA Chisel specifications — Explicit sequence constraints, including codon choices and translation preservation.
- LinearDesign — Joint optimization of codon adaptation and a thermodynamic RNA-folding objective.
- ViennaRNA — RNA structure analysis using thermodynamic models; the benchmark’s pair-count and additive-score exercises use simpler rules.
- Primer3 — Primer selection with melting-temperature, complementarity, and pair-quality criteria.
- GoldenMutagenesis domestication — Silent removal of internal cleavage sites for Golden Gate assembly.
- Twist gene-design resources — Synthesis complexity associated with sequence repeats, homopolymers, and GC extremes.
- Codon Statistics Database — Comparative codon-usage statistics, including GC and third-position GC.
- ExPASy ProtParam documentation — Protein composition, hydropathy, theoretical pI, and other sequence descriptors.
- ExPASy PeptideMass documentation — Theoretical proteolytic digests and peptide masses for protein identification.
- NIST Atomic Weights and Isotopic Compositions — Source of the fixed 12C, 1H, 14N, 16O, and 32S central masses used to derive the residue and water constants; snapshot accessed 2 November 2026. The mass reference entry records the derivation and numerical convention.
- PROSITE N-glycosylation pattern — The sequon pattern and the distinction between a candidate site and actual modification.
- Cytiva ion-exchanger selection guide — Protein charge, pI, operating pH, and ion-exchange resin selection.
- RNA and mRNA sequence mapping by mass spectrometry — RNase digestion, fragment identification, and complementary mapping information for RNA characterization.
- NUPACK documentation — Thermodynamic analysis and design of nucleic-acid structures and interacting complexes.
- CHARMING — Harmonizing synonymous codon usage to reproduce a desired usage pattern.
- Restriction-site markers in engineered alleles — An example of adding a silent restriction site to help identify a desired genome edit.
- Origin and evolution of the zinc finger antiviral protein — A biological example of RNA recognition sensitive to CpG dinucleotides.
- RNAi-resistant rescue in a B-cyclin study — Synonymous changes used to make rescue cDNAs resistant to the corresponding RNAi reagents.
- Coding-sequence determinants of expression — A synonymous GFP library illustrates experimentally varying coding RNA while preserving the protein; it is not the benchmark’s exact CG/GC-controlled panel.
- Site-directed mutagenesis protocol — Point mutations, deletions, and other explicitly designed sequence changes.
- Addgene bacterial expression collection — Examples of protein-expression constructs with fusion and purification tags.
- Removal of affinity tags with TEV protease — TEV-mediated tag removal and the resulting protein products.
- SwiftLib — Degenerate-codon-library optimization for desired amino-acid coverage and manageable library size.
- RNase T1: enzyme specificity and applications — Thermo Fisher’s enzyme documentation: guanosine-specific cleavage of single-stranded RNA; fungal origin and RNA-analysis uses.
- EcoRI recognition and cleavage site — A real restriction enzyme recognizing GAATTC; cleavage is G/AATTC.
- Kyte–Doolittle hydropathy scale — The original experimentally informed scale for displaying hydrophilic and hydrophobic regions of proteins.
- Structural basis for microRNA targeting — Argonaute uses guide RNA base pairing to recognize target mRNA; a uniform mismatch count is a simpler benchmark rule.
- Nussinov and colleagues: Algorithms for Loop Matchings — The 1978 dynamic-programming treatment of noncrossing base-pair matching, a historical foundation for simplified RNA-folding problems.
- ApoB RNA editing: CAA becomes a stop codon — Experimental C-to-U RNA editing changes a glutamine CAA codon to UAA in apolipoprotein B mRNA.
- The apoB-editing catalytic subunit is a cytidine deaminase — Identification of the enzyme chemistry underlying apoB RNA editing.
- Programmable editing by endogenous ADAR — Primary research on ADAR-catalyzed adenosine-to-inosine editing. The benchmark’s translation-only example represents the recoding as A→G.
- Synonymous mutations and restoration of mRNA base pairing — The rpsT study found that compensatory synonymous substitutions restoring predicted pairing could partly or fully restore fitness in some tested mutants.
- NCBI CDKN2A annotation — p16INK4a and p14ARF transcripts share a second exon read in different frames, providing a concrete biological example of overlapping coding information.
- Imaging individual mRNA molecules with labeled probes — Primary research on detecting mRNA through complementary oligonucleotide probes; assay chemistry and fluorescence are outside the benchmark.
- His6-tagged protein purification — A laboratory teaching resource explaining binding of a six-histidine tag to nickel affinity material.
- Ensembl calculated variant consequences — Rule-based annotation using codons and amino acids, with synonymous, missense, stop-gained, and frameshift consequence categories.
Evaluation design
Paired prompts, separate score axes
Each underlying instance gets easy and hard prompts with one shared answer and validator. Track reference support separately from sequence length, number of edits, constraint density, or search-space size. Keep tool access and token budgets matched.
Report canonical final-answer accuracy and answer-format compliance separately. A correct answer must match the normalized reference, including every requested field. Intermediate results may also receive diagnostic scores; a plausible explanation cannot rescue a wrong final answer.
Prevent sequence leakage
Split related sequence families before deriving tasks. Keep parent CDSs, homologs, recodings, mutants, RNA products, protein products, and composed examples in the same partition.
Hold out selected task combinations as a separate composition-generalization test. Do not use the exact intermediate sequences from a held-out composition to train its individual tasks.
Certify reference answers
Generate one canonical reference answer per instance, including every tie-break. Independently verify protein preservation, all constraints, and the required selection rule. Keep exact-search instances small enough to certify the chosen feasible or optimal answer, not just one witness.
A reference may say IMPOSSIBLE only after an independent solver certifies infeasibility. NONE means no qualifying readout exists. A search timeout establishes neither result.
Status of this proposal
This document defines candidate task types, prompt templates, and scoring rules. It does not claim that a dataset, reference implementation, solver, or benchmark score already exists.
Before release: generate instances, implement reference solvers and independent validators, verify canonical-answer uniqueness and easy/hard equivalence, and pilot task lengths and search limits. The illustrative examples have been checked; they are not a released benchmark dataset.