Skip to main content
Challenge

Build a Protein Accession Translation Conformance Auditor

Cross-reference NCBI protein fasta records against CDS translation products using Biopython. Convert validated peptide sequences and mismatch scores into FHIR Molecular Observation entries.

Data ScienceHosted by Vera
Challenge brief

What you are building

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

Cross-reference NCBI protein fasta records against CDS translation products using Biopython. Convert validated peptide sequences and mismatch scores into FHIR Molecular Observation entries.

Genomic Translation Specialist

Ingest CDS and protein FASTA sequences from an NCBI Datasets gene archive.

Translate nucleotide coding sequences into amino acid strings using standard Biopython codon tables.

Compute sequence alignment identity between translated CDS and RefSeq protein records.

Format verified identity percentages into FHIR Molecular Observation bundles for export.

Terminal CLI and static web viewer showing sequence identity scores, translation offsets, and validation status.

Use synthetic FASTA pairs derived from NCBI Datasets human TP53 test packages stored in a mock test directory. Starter examples below are synthetic. They are not downloaded records.

Biopython Uses Biopython computational molecular biology routines to perform nucleotide translation and pairwise sequence comparisons.

ollama, biopython, click. ollama runs lightweight local open-source LLMs to classify biological mutation notes into FHIR observation annotations. Local Ollama instance serving a 7B-8B parameter model alongside local Python 3.12 environment.

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.

Biopython translation accurately reproduces protein sequence for standard transcripts.

Generate FHIR Observation with component identity percentage matching computed alignment score.

Route sequences exhibiting less than 99% peptide identity to manual review.

```json [ { "input": { "cds_id": "NM_000546.6_cds", "protein_id": "NP_000537.3", "cds_sequence": "ATGGAGGAGCCGCAGTCAGATCCTAGCGTCGAGCCCCCTCTGAGTCAGGAAACATTTTCAGACCTATGGAAACTACTTCCTGAAAACAACGTTCTGTCCCCCTTGCCGTCCCAAGCAATGGATGATTTGATGCTGTCCCCGGACGATATTGAACAATGGTTCACTGAAGACCCAGGTCCAGATGAAGCTCCCAGAATGCCAGAGGCTGCTCCCCGCGTGGCCCCTGCACCAGCAGCTCCTACACCGGCGGCCCCTGCACCAGCCCCCTCCTGGCCCCTGTCATCTTCTGTCCCTTCCCAGAAAACCTACCAGGGCAGCTACGGTTTCCGTCTGGGCTTCTTGCATTCTGGGACAGCCAAGTCTGTGACTTGCACGTACTCCCCTGCCCTCAACAAGATGTTTTGCCAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGTTGATTCCACACCCCCGCCCGGCACCCGCGTCCGCGCCATGGCCATCTACAAGCAGTCACAGCACATGACGGAGGTTGTGAGGCGCTGCCCCCACCATGAGCGCTGCTCAGATAGCGATGGTCTGGCCCCTCCTCAGCATCTTATCCGAGTGGAAGGAAATTTGCGTGTGGAGTATTTGGATGACAGAAACACTTTTCGACATAGTGTGGTGGTGCCCTATGAGCCGCCTGAGGTTGGCTCTGACTGTACCACCATCCACTACAACTACATGTGTAACAGTTCCTGCATGGGCGGCATGAACCGGAGGCCCATCCTCACCATCATCACACTGGAAGACTCCAGTGGTAATCTACTGGGACGGAACAGCTTTGAGGTGCGTGTTTGTGCCTGTCCTGGGAGAGACCGGCGCACAGAGGAAGAGAATCTCCGCAAGAAAGGGGAGCCTCACCACGAGCTGCCCCCAGGGAGCACTAAGCGAGCACTGCCCAACAACACCAGCTCCTCTCCCCAGCCAAAGAAGAAACCACTGGATGGAGAATATTTCACCCTTCAGATCCGTGGGCGTGAGCGCTTCGAGATGTTCCGAGAGCTGAATGAGGCCTTGGAACTCAAGGATGCCCAGGCTGGGAAGGAGCCAGGGGGGAGCAGGGCTCACTCCAGCCACCTGAAGTCCAAAAAGGGTCAGTCTACCTCCCGCCATAAAAAACTCATGTTCAAGACAGAAGGGCCTGACTCAGACTGA", "protein_sequence": "MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGPDEAPRMPEAAPPVAPAPAAPTPAAPAPAPSWPLSSSVPSQKTYQGSYGFRLGFLHSGTAKSVTCTYSPALNKMFCQLAKTCPVQLWVDSTPPPGTRVRAMAIYKQSQHMTEVVRRCPHHERCSDSDGLAPPQHLIRVEGNLRVEYLDDRNTFRHSVVVPYEPPEVGSDCTTIHYNYMCNSSCMGGMNRRPILTIITLEDSSGNLLGRNSFEVRVCACPGRDRRTEEENLRKKGEPHHELPPGSTKRALPNNTSSSPQPKKKPLDGEYFTLQIRGRERFEMFRELNEALELKDAQAGKEPGGSRAHSSHLKSKKGQSTSRHKKLMFKTEGPDSD" }, "expected_output": { "cds_id": "NM_000546.6_cds", "protein_id": "NP_000537.3", "translation_match": true, "identity_percent": 100, "fhir_observation": { "resourceType": "Observation", "status": "final", "valueQuantity": { "value": 100, "unit": "%" } } } }, { "input": { "cds_id": "NM_000546.6_cds_err", "protein_id": "NP_000537.3", "cds_sequence": "ATGGAGGAGCCGCAGTCAGATCCTAGCGTCGAGCCCCCTCTGAGTCAGGAAACATTTTCA", "protein_sequence": "MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGP" }, "expected_output": { "cds_id": "NM_000546.6_cds_err", "protein_id": "NP_000537.3", "translation_match": false, "identity_percent": 33.33, "fhir_observation": { "resourceType": "Observation", "status": "preliminary", "valueQuantity": { "value": 33.33, "unit": "%" } } } } ] ```

Strictly research compute evaluating nucleotide-to-peptide translation consistency. No diagnostic interpretation or medical recommendation. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Strictly research compute evaluating nucleotide-to-peptide translation consistency. No diagnostic interpretation or medical recommendation. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Biopython translation accurately reproduces protein sequence for standard transcripts. Generate FHIR Observation with component identity percentage matching computed alignment score. Route sequences exhibiting less than 99% peptide identity to manual review.

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

Ingest CDS and protein FASTA sequences from an NCBI Datasets gene archive. Translate nucleotide coding sequences into amino acid strings using standard Biopython codon tables. Compute sequence alignment identity between translated CDS and RefSeq protein records. Format verified identity percentages into FHIR Molecular Observation bundles for export.

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

Biopython translation accurately reproduces protein sequence for standard transcripts. Generate FHIR Observation with component identity percentage matching computed alignment score. Route sequences exhibiting less than 99% peptide identity to manual review.

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

Terminal CLI and static web viewer showing sequence identity scores, translation offsets, and validation status.

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

Strictly research compute evaluating nucleotide-to-peptide translation consistency. No diagnostic interpretation or medical recommendation.

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

  • Ingest CDS and protein FASTA sequences from an NCBI Datasets gene archive.

  • Translate nucleotide coding sequences into amino acid strings using standard Biopython codon tables.

  • Compute sequence alignment identity between translated CDS and RefSeq protein records.

  • Format verified identity percentages into FHIR Molecular Observation bundles for export.

Resources and assets

Reference links and supporting material

Dataset notes

Use synthetic FASTA pairs derived from NCBI Datasets human TP53 test packages stored in a mock test directory. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Ollama

Local LLM runtime for offline inference.

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest CDS and protein FASTA sequences from an NCBI Datasets gene archive. Translate nucleotide coding sequ...
  • Biopython translation accurately reproduces protein sequence for standard transcripts. Generate FHIR Observ...
  • Terminal CLI and static web viewer showing sequence identity scores, translation offsets, and validation st...
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

Policy Serving
  • Ollama · 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 Protein Accession Translation Conformance Auditor