Build a Multi-Transcript Coding Frame and Peptide Translation Auditor
Inspect coding sequence coordinates across multi-transcript gene packages to identify translational frame shifts. Generate structured FHIR Observation payloads tracking open reading frame integrity.
What you are building
The core problem, expected build, and operating context for this challenge.
Inspect coding sequence coordinates across multi-transcript gene packages to identify translational frame shifts. Generate structured FHIR Observation payloads tracking open reading frame integrity.
Functional Genomics Biocurator
Load CDS and protein sequences from NCBI gene packages using Biopython.
Translate nucleotide CDS records across all three reading frames using the standard translation table.
Identify reading frame alignments that produce exact peptide matches against NCBI RefSeq protein records.
Generate FHIR Observation resources documenting reading frame validity and detected stop anomalies.
FastAPI backend serving JSON inspection endpoints and an HTML table displaying frame translation alignments.
Download human BRCA1 gene packages using NCBI Datasets CLI --include cds,protein into local sandbox folders. Starter examples below are synthetic. They are not downloaded records.
NCBI Datasets gene download Processes CDS and protein sequences retrieved via NCBI Datasets --include cds,protein parameters.
pydantic-ai, biopython, fastapi. Pydantic AI guarantees type constraints and schema enforcement for complex translation and reading frame models. Lightweight API or local model to generate structured explanations of frame-shift causes.
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 Biopython Seq.translate and compares with target protein sequences.
Identifies reading frame offset (frame 0, +1, or +2) matching the documented protein product.
Outputs compliant FHIR R5 Observation records with appropriate status codes and valueCodings.
```json [ { "input": { "transcript_id": "NM_0001", "cds_seq": "ATGGCCAACGTATAG", "expected_protein": "MANV" }, "expected_output": { "frame_offset": 0, "exact_match": true, "fhir_observation": { "resourceType": "Observation", "status": "final", "code": { "coding": [ { "system": "http://hl7.org/fhir/sid/ncbi-gene", "code": "NM_0001" } ] }, "valueString": "In-frame translation confirmed with matching protein accession" } } }, { "input": { "transcript_id": "NM_0002", "cds_seq": "TGGCCAACGTATAG", "expected_protein": "MANV" }, "expected_output": { "frame_offset": null, "exact_match": false, "fhir_observation": { "resourceType": "Observation", "status": "preliminary", "code": { "coding": [ { "system": "http://hl7.org/fhir/sid/ncbi-gene", "code": "NM_0002" } ] }, "valueString": "Frame shift or missing start codon: no reading frame matched MANV" } } } ] ```
Uses open-access reference transcript sequences without individual patient exposure or clinical claims. Use mock external writes. Require human review before any real deployment.
Participation guide
Uses open-access reference transcript sequences without individual patient exposure or clinical claims. Use mock external writes and human review.
How work is evaluated
Translates CDS sequences using Biopython Seq.translate and compares with target protein sequences. Identifies reading frame offset (frame 0, +1, or +2) matching the documented protein product. Outputs compliant FHIR R5 Observation records with appropriate status codes and valueCodings.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Load CDS and protein sequences from NCBI gene packages using Biopython. Translate nucleotide CDS records across all three reading frames using the standard translation table. Identify reading frame alignments that produce exact peptide matches against NCBI RefSeq protein records. Generate FHIR Observation resources documenting reading frame validity and detected stop anomalies.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Translates CDS sequences using Biopython Seq.translate and compares with target protein sequences. Identifies reading frame offset (frame 0, +1, or +2) matching the documented protein product. Outputs compliant FHIR R5 Observation records with appropriate status codes and valueCodings.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
FastAPI backend serving JSON inspection endpoints and an HTML table displaying frame translation alignments.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Uses open-access reference transcript sequences without individual patient exposure or clinical claims.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Load CDS and protein sequences from NCBI gene packages using Biopython.
Translate nucleotide CDS records across all three reading frames using the standard translation table.
Identify reading frame alignments that produce exact peptide matches against NCBI RefSeq protein records.
Generate FHIR Observation resources documenting reading frame validity and detected stop anomalies.
Reference links and supporting material
Download human BRCA1 gene packages using NCBI Datasets CLI `--include cds,protein` into local sandbox folders. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Pydantic AI
Typed Python agent framework.
Evaluated output
No output checks are configured.
- Load CDS and protein sequences from NCBI gene packages using Biopython. Translate nucleotide CDS records ac...
- Translates CDS sequences using Biopython Seq.translate and compares with target protein sequences. Identifi...
- FastAPI backend serving JSON inspection endpoints and an HTML table displaying frame translation alignments.
- 2 public reference cases
- 2 configured tools
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
- Pydantic AI · Optional
- Pydantic AI · 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.