alterlab-bioservices

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:

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:

from bioservices import KEGG

k = KEGG()
k.organism = "hsa"  # Set to human

# Search for organisms
k.lookfor_organism("droso")  # Find Drosophila species

# Find pathways by name
k.lookfor_pathway("B cell")  # Returns matching pathway IDs

# Get pathways containing specific genes
pathways = k.get_pathway_by_gene("7535", "hsa")  # ZAP70 gene

# Retrieve and parse pathway data
data = k.get("hsa04660")
parsed = k.parse(data)

# Extract pathway interactions
interactions = k.parse_kgml_pathway("hsa04660")
relations = interactions['relations']  # Protein-protein interactions

# Convert to Simple Interaction Format
sif_data = k.pathway2sif("hsa04660")