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Challenge

Build a Gene Package CDS Extraction and Reading Frame Evaluator

Process gene data packages containing CDS and protein fasta files to verify translation coordinates. Compare Biopython translation products with expected NCBI RefSeq protein records.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Process gene data packages containing CDS and protein fasta files to verify translation coordinates. Compare Biopython translation products with expected NCBI RefSeq protein records.

Bioinformatics Assay Specialist

Download or mock NCBI Datasets gene data packages with gene, CDS, and protein records.

Extract coding sequences and translate nucleotides to amino acids using Biopython.

Compare translated sequence with provided protein accessions to detect truncation or mismatches.

Produce a structured JSON report documenting codon discrepancies and translation fidelity.

Command-line tool generating summary JSON and markdown verification tables.

Execute 'datasets download gene gene-id 672 --include cds,protein' to get reference files, or use local mock fixtures. Starter examples below are synthetic. They are not downloaded records.

NCBI Datasets gene download Extracts CDS and protein files specifically from NCBI Datasets packages using the --include flag specification.

mlflow, biopython, click. MLflow tracks translation fidelity experiments, parameter runs, and discrepancy metrics across gene packages. None mandatory; rule-based sequence logic with optional local LLM for mutation discrepancy annotation.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Translates CDS sequences using standard genetic codes in Biopython.

Identifies premature stop codons and mismatching translation products.

Logs experiment runs and discrepancy counts to an MLflow tracking server.

```json [ { "input": { "gene_symbol": "TEST1", "cds_seq": "ATGGCCAACGTCTAA", "expected_protein": "MANV" }, "expected_output": { "match": true, "translated_protein": "MANV*", "premature_stop": false, "discrepancies": [] } }, { "input": { "gene_symbol": "TEST2", "cds_seq": "ATGTAACCAACGTCTAA", "expected_protein": "MANV" }, "expected_output": { "match": false, "translated_protein": "M*PT", "premature_stop": true, "discrepancies": [ "Stop codon at residue 2" ] } } ] ```

Analytical translation verification pipeline operating on non-clinical biological sequences. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Analytical translation verification pipeline operating on non-clinical biological sequences. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Translates CDS sequences using standard genetic codes in Biopython. Identifies premature stop codons and mismatching translation products. Logs experiment runs and discrepancy counts to an MLflow tracking server.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Download or mock NCBI Datasets gene data packages with gene, CDS, and protein records. Extract coding sequences and translate nucleotides to amino acids using Biopython. Compare translated sequence with provided protein accessions to detect truncation or mismatches. Produce a structured JSON report documenting codon discrepancies and translation fidelity.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Translates CDS sequences using standard genetic codes in Biopython. Identifies premature stop codons and mismatching translation products. Logs experiment runs and discrepancy counts to an MLflow tracking server.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Command-line tool generating summary JSON and markdown verification tables.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Analytical translation verification pipeline operating on non-clinical biological sequences.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Download or mock NCBI Datasets gene data packages with gene, CDS, and protein records.

  • Extract coding sequences and translate nucleotides to amino acids using Biopython.

  • Compare translated sequence with provided protein accessions to detect truncation or mismatches.

  • Produce a structured JSON report documenting codon discrepancies and translation fidelity.

Resources and assets

Reference links and supporting material

Dataset notes

Execute 'datasets download gene gene-id 672 --include cds,protein' to get reference files, or use local mock fixtures. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

MLflow

MLOps

Evaluated output

No output checks are configured.

Evaluation checks
  • Download or mock NCBI Datasets gene data packages with gene, CDS, and protein records. Extract coding seque...
  • Translates CDS sequences using standard genetic codes in Biopython. Identifies premature stop codons and mi...
  • Command-line tool generating summary JSON and markdown verification tables.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 1 configured tool

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • MLflow · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Gene Package CDS Extraction and Reading Frame Evaluator