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Challenge

Build a Prokaryotic RefSeq Annotation and Slippage Discrepancy Detector

Evaluate prokaryotic WP_ accession metadata and FASTA files to detect ribosomal slippage annotation gaps. Generate structured FHIR DiagnosticReport payloads for microbiological biocurators.

Data ScienceHosted by Vera
Challenge brief

What you are building

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

Evaluate prokaryotic WP_ accession metadata and FASTA files to detect ribosomal slippage annotation gaps. Generate structured FHIR DiagnosticReport payloads for microbiological biocurators.

Microbiology Data Specialist

Ingest prokaryotic gene packages containing WP_ accessions and gene metadata using Biopython.

Inspect coding coordinates for internal stop codons indicating programmatic translation exceptions or frameshifts.

Verify whether ribosomal slippage exceptions are explicitly cataloged in the gene data report.

Assemble findings into FHIR DiagnosticReport resources linking affected prokaryotic accessions.

CLI utility with terminal summary tables and automated JSON artifact dispatch to local filesystem.

Query bacterial gene packages using NCBI Datasets CLI with taxon identifiers and WP_ accession filters in sandbox test environments. Starter examples below are synthetic. They are not downloaded records.

NCBI Datasets gene download Leverages NCBI Datasets prokaryotic gene package rules specifying WP_ accessions with gene and protein sequences.

dspy, biopython, pydantic. DSPy compiles robust prompt pipelines to classify biological annotations against structured taxonomy categories without brittle prompt templates. Local or hosted API LLM capable of rule-grounded categorization and structured summary generation.

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.

Accurately flags internal stop codons in prokaryotic nucleotide records when translating via standard genetic code.

Identifies documented translational exceptions in gene package metadata vs undocumented coordinate anomalies.

Generates valid FHIR DiagnosticReport JSON containing observation references for flagged accessions.

```json [ { "input": { "accession": "WP_000123456.1", "nucleotide_seq": "ATGCGCTAATGA", "slippage_annotated": true }, "expected_output": { "slippage_detected": true, "annotation_status": "documented", "review_recommended": false, "fhir_diagnostic_report": { "resourceType": "DiagnosticReport", "status": "final", "conclusion": "Documented ribosomal slippage observed in WP_000123456.1." } } }, { "input": { "accession": "WP_000987654.1", "nucleotide_seq": "ATGCGCTAATGA", "slippage_annotated": false }, "expected_output": { "slippage_detected": true, "annotation_status": "undocumented", "review_recommended": true, "fhir_diagnostic_report": { "resourceType": "DiagnosticReport", "status": "registered", "conclusion": "Undocumented internal stop codon detected in WP_000987654.1. Curator inspection needed." } } } ] ```

Operates entirely on unclassified prokaryotic reference records without real biological sample processing. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Operates entirely on unclassified prokaryotic reference records without real biological sample processing. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Accurately flags internal stop codons in prokaryotic nucleotide records when translating via standard genetic code. Identifies documented translational exceptions in gene package metadata vs undocumented coordinate anomalies. Generates valid FHIR DiagnosticReport JSON containing observation references for flagged accessions.

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 prokaryotic gene packages containing WP_ accessions and gene metadata using Biopython. Inspect coding coordinates for internal stop codons indicating programmatic translation exceptions or frameshifts. Verify whether ribosomal slippage exceptions are explicitly cataloged in the gene data report. Assemble findings into FHIR DiagnosticReport resources linking affected prokaryotic accessions.

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

Accurately flags internal stop codons in prokaryotic nucleotide records when translating via standard genetic code. Identifies documented translational exceptions in gene package metadata vs undocumented coordinate anomalies. Generates valid FHIR DiagnosticReport JSON containing observation references for flagged accessions.

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

CLI utility with terminal summary tables and automated JSON artifact dispatch to local filesystem.

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

Operates entirely on unclassified prokaryotic reference records without real biological sample processing.

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 prokaryotic gene packages containing WP_ accessions and gene metadata using Biopython.

  • Inspect coding coordinates for internal stop codons indicating programmatic translation exceptions or frameshifts.

  • Verify whether ribosomal slippage exceptions are explicitly cataloged in the gene data report.

  • Assemble findings into FHIR DiagnosticReport resources linking affected prokaryotic accessions.

Resources and assets

Reference links and supporting material

Dataset notes

Query bacterial gene packages using NCBI Datasets CLI with taxon identifiers and WP_ accession filters in sandbox test environments. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

DSPy

Prompt and LM program optimization framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest prokaryotic gene packages containing WP_ accessions and gene metadata using Biopython. Inspect codin...
  • Accurately flags internal stop codons in prokaryotic nucleotide records when translating via standard genet...
  • CLI utility with terminal summary tables and automated JSON artifact dispatch to local filesystem.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 3 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

Action Space
  • DSPy · Optional
Training Infra
  • DSPy · Optional
Orchestration
  • DSPy · 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 Prokaryotic RefSeq Annotation and Slippage Discrepancy Detector