# Bioservices

Unified Python interface to 40+ bioinformatics services.

- Repository: https://github.com/synthetic-sciences/openscience (4321 stars)
- Category: Data and ML
- License: GPLv3 license
- Last updated: 2026-10-30
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add synthetic-sciences/openscience --skill bioservices -g -a claude-code -y`
Codex: `npx skills add synthetic-sciences/openscience --skill bioservices -g -a codex -y`
Cursor: `npx skills add synthetic-sciences/openscience --skill bioservices -g -a cursor -y`
Gemini CLI: `npx skills add synthetic-sciences/openscience --skill bioservices -g -a gemini-cli -y`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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.

## 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 alignment)
- Querying gene ontology terms (QuickGO, GO annotations)
- Accessing protein-protein interaction data (PSICQUIC, IntactComplex)
- Mining genomic data (BioMart, ArrayExpress, ENA)
- Integrating data from multiple bioinformatics resources in a single workflow

## Core Capabilities

### 1. Protein Analysis

Retrieve protein information, sequences, and functional annotations:

```python
from bioservices import UniProt

u = UniProt(verbose=False)

# Search for protein by name
results = u.search("ZAP70_HUMAN", frmt="tab", columns="id,genes,organism")

# Retrieve FASTA sequence
sequence = u.retrieve("P43403", "fasta")

# Map identifiers between databases
kegg_ids = u.mapping(fr="UniProtKB_AC-ID", to="KEGG", query="P43403")
```

**Key methods:**
- `search()`: Query UniProt with flexible search terms
- `retrieve()`: Get protein entries in various formats (FASTA, XML, tab)
- `mapping()`: Convert identifiers between databases

Reference: `references/services_reference.md` for complete UniProt API details.

### 2. Pathway Discovery and Analysis

Access KEGG pathway information for genes and organisms:

```python
from bioservices import KEGG

The rest: https://github.com/synthetic-sciences/openscience/blob/HEAD/backend/cli/skills/biology/bioservices/SKILL.md