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gene-database

Retrieve gene metadata from NCBI Gene databases by symbol or ID.

1|Updated Mar 19, 2026
Search Tags:#genomics#batch#ncbi#annotation#datasets#eutilities#gene
One-click install
npx skills add https://github.com/JosephWoodall/noosphere --skill gene-database-josephwoodall
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gene-database
Source: https://github.com/JosephWoodall/noosphere/tree/main/.agent/skills/gene-database
Command: npx skills add https://github.com/JosephWoodall/noosphere --skill gene-database-josephwoodall

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Researchers and data scientists need a reliable way to access and consolidate gene metadata from NCBI Gene, including gene symbols, IDs, RefSeqs, GO annotations, chromosomal locations, and phenotypes, across multiple organisms.

Core Features & Use Cases

  • Search by gene symbol or ID across organisms using NCBI's E-utilities and Datasets API to resolve IDs and collect key metadata.
  • Batch lookups to annotate gene lists with symbols, descriptions, taxon information, chromosomal data, RefSeqs, GO annotations, and transcript data for downstream analyses.
  • Use cases include building gene annotation tables, validating gene lists for pipelines, and enriching datasets for functional genomics studies.

Quick Start

Run the batch_gene_lookup.py script with a file of gene symbols and the target organism to produce a JSON summary of gene IDs and basic metadata.

Frequently Asked Questions about gene-database

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve gene information from NCBI using gene symbols or IDs?▼

You retrieve gene information by querying NCBI Gene databases via E-utilities and Datasets API using gene symbols or IDs. This returns identifiers, descriptions, chromosomal locations, RefSeqs, GO annotations, and transcript data as structured JSON output for downstream analyses.

Can I batch process a list of gene symbols to annotate them with RefSeqs and GO annotations?▼

Yes, you can run batch lookups to annotate gene lists with symbols, descriptions, taxon information, chromosomal data, RefSeqs, GO annotations, and transcript data. Supply a file of gene symbols and the target organism to produce a structured JSON summary.

What is the best way to search for gene metadata across multiple organisms?▼

The best way to search for gene metadata across multiple organisms is using NCBI E-utilities and Datasets API. This approach resolves gene IDs and collects key metadata while enforcing input validation, error handling, and rate-limited API access for reliable integration.

Does this NCBI gene query approach handle rate limiting and input validation?▼

Yes, this approach to querying NCBI Gene data enforces input validation, error handling, and rate-limited API access. These constraints ensure reliable data retrieval and structured JSON output suitable for integration into analytics pipelines.

Why use structured JSON output for NCBI gene annotation data?▼

Structured JSON output for NCBI gene annotation data ensures seamless integration into downstream analytics pipelines. It consolidates gene symbols, IDs, RefSeqs, GO annotations, and chromosomal locations into a machine-readable format for functional genomics studies.

When do I need to validate gene lists for bioinformatics pipelines?▼

You need to validate gene lists for bioinformatics pipelines when preparing data for functional genomics studies. Querying NCBI Gene data resolves symbols to IDs and collects metadata like RefSeqs and GO annotations, ensuring your dataset is accurate and enriched.

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