bioservices
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
npx skills add K-Dense-AI/scientific-agent-skills --skill bioservices --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# BioServices ## Overview BioServices is a Python package providing programmatic access to approximately 40 bioinformatics web services and databases. Retrieve biological data, perform cross-database queries, map identifiers, analyze sequences, and integrate multiple biological resources in Python workflows. The package handles both REST and SOAP/WSDL protocols transparently. **Version note:** Examples target **bioservices 1.16.0** (PyPI, Mar 2026). Requires **Python 3.9–3.12**. UniProt REST changes in mid-2022 (bioservices ≥1.10) mainly affect tabular `columns` names — see upstream `_legacy_names` if parsing breaks. ChEMBL wrappers changed at 1.6.0 (2018 API); use `get_similarity`, `get_substructure`, `get_molecule` instead of pre-1.6 method names. ## When to Use This Skill This skill should be used when: - Retrieving protein sequences, annotations, or structures from UniProt, PDB, Pfam - Analyzing metabolic pathways and gene functions via KEGG or Reactome - Searching compound databases (ChEBI, ChEMBL, PubChem) for chemical information - Converting identifiers between different biological databases (KEGG↔UniProt, compound IDs) - Running sequence similarity searches (BLAST, MUSCLE
- Overview
- When to Use This Skill
- Core Capabilities
- 1. Protein Analysis
- 2. Pathway Discovery and Analysis
- 3. Compound Database Searches
- 4. Sequence Analysis
- 5. Identifier Mapping
- 6. Gene Ontology Queries
- 7. Protein-Protein Interactions
- Multi-Service Integration Workflows
- Complete Protein Analysis Pipeline
- Pathway Network Analysis
- Cross-Database Compound Search
export NCBI_EMAIL=your.email@example.com python scripts/protein_analysis_workflow.py ZAP70_HUMAN Or pass email as optional second argument if NCBI_EMAIL is unset python scripts/protein_analysis_workflow.py ZAP70_HUMAN your.email@example.com python scripts/pathway_analysis.py hsa output_directory/ python scripts/compound_cross_reference.py Geldanamycin python scripts/batch_id_converter.py input_ids.txt --from UniProtKB_AC-ID --to KEGG uv pip install "bioservices==1.16.0"
What does the bioservices skill do?
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill bioservices --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.