1. Quick Start

1.1. Introduction

BioServices lets you query biological databases from Python with no manual HTTP requests, no XML parsing, and no API key juggling. You import a class, call a method, and get back a Python object (usually a dictionary or a pandas.DataFrame).

The pattern is always the same:

from bioservices import UniProt       # import the service class
u = UniProt()                         # create an instance (opens no connection yet)
result = u.search("ZAP70_HUMAN")     # call a method — data comes back as Python objects

The sections below walk through a handful of services to give you a feel for what is possible. The reference guide documents every class and method in full detail, and the tutorials go deeper on KEGG, BioModels, and compound look-up workflows.

1.2. UniProt

UniProt gives you programmatic access to the UniProt Knowledgebase: full-text search, sequence retrieval, and cross-database ID mapping.

Map an accession to another database

>>> from bioservices import UniProt
>>> u = UniProt(verbose=False)
>>> u.mapping(fr="UniProtKB_AC-ID", to="KEGG", query="P43403")
{'results': [{'from': 'P43403', 'to': 'hsa:7535'}]}

Retrieve a FASTA sequence:

>>> fasta = u.retrieve("P09958", frmt="fasta")
>>> print(fasta[:60])
>sp|P09958|FURIN_HUMAN Furin OS=Homo sapiens OX=9606 GN=FURIN

Search and get a DataFrame:

>>> df = u.search("ZAP70+AND+organism_id:9606", frmt="tsv",
...               columns="accession,gene_names,length", limit=5)

See also

bioservices.uniprot.UniProt

1.3. KEGG

KEGG wraps the KEGG REST API, giving access to pathways, genes, compounds, reactions, and more across hundreds of organisms.

from bioservices import KEGG
k = KEGG(verbose=False)

Set the organism to human and explore pathways:

k.organism = "hsa"            # Homo sapiens
print(k.pathwayIds[:5])       # first five human pathway IDs

Retrieve the full entry for a gene or pathway:

print(k.get("hsa:3586"))          # IL6 gene
print(k.get("path:hsa05416"))     # Viral myocarditis pathway

Convert between KEGG and UniProt IDs:

>>> from bioservices import KEGG
>>> k = KEGG(verbose=False)
>>> k.code2Tnumber("hsa")
'T01001'

1.4. QuickGO

QuickGO provides access to Gene Ontology terms and annotations from the EBI QuickGO browser.

Look up a GO term:

from bioservices import QuickGO
g = QuickGO(verbose=False)
res = g.get_go_terms("GO:0003824")
print(res[0]["name"])              # catalytic activity

Search GO terms by keyword:

hits = g.go_search("apoptosis")
for term in hits[:3]:
    print(term["id"], term["name"])

Retrieve annotations for a gene product:

ann = g.Annotation(geneProductId="UniProtKB:P12345", limit=10)

See also

bioservices.quickgo.QuickGO

1.5. BioModels

BioModels provides access to the EBI BioModels database of curated mathematical models of biological processes.

from bioservices import BioModels
b = BioModels()
model = b.get_model("BIOMD0000000299")   # retrieve a curated SBML model

List all available model IDs and search by keyword:

ids = b.get_models_by_search("glucose", offset=0, numResults=10)

1.6. Rhea

Rhea is a reaction database where all participants are linked to ChEBI, with cross-references to KEGG, MetaCyc, and Reactome.

Search by keyword (wildcards supported):

from bioservices import Rhea
r = Rhea()
df = r.search("caffeine")          # returns a pandas DataFrame
print(df[["RHEA ID", "Equation"]].head())

Retrieve a specific reaction:

df = r.query("RHEA:10280", columns="rhea-id,equation")

See also

bioservices.rhea.Rhea

1.7. Other services

BioServices wraps many more databases — ChEMBL, ChEBI, Reactome, PDB, PDBe, EUtils, Ensembl, STRING, GEO, PRIDE, WikiPathways, and others. Each follows the same pattern: import, instantiate, call a method.

The reference guide lists every available service with full API documentation. If you need a service that is not yet wrapped, the Developer Guide section shows how to add one in a few lines using the REST base class.