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biocontext-knowledge-queries

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BioContext knowledge: UniProt, AlphaFold, STRING, Reactome, GO, PanglaoDB, PubMed, OpenTargets queries via ov.biocontext for gene annotation.

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BioContext Knowledge Queries

Use this skill when the user wants to look up gene/protein annotations, query pathway databases, find cell type markers, search biomedical literature, or explore drug-disease associations. BioContext provides programmatic access to 49 biomedical databases through a unified Python API.

This is a knowledge integration layer — use it to annotate analysis results (e.g., annotate DEG lists with protein function, find pathways for gene clusters, validate marker genes against PanglaoDB).

Available Functions by Category

Protein & Genomics

FunctionDatabaseReturns
query_uniprot(gene_symbol, species)UniProtProtein function, domains, GO terms, references
get_uniprot_id(protein_symbol, species)UniProtUniProt accession ID
query_alphafold(protein_symbol, species)AlphaFoldPredicted 3D structure, confidence scores
get_ensembl_id(gene_symbol, species)EnsemblEnsembl gene ID (ENSG...)
query_interpro(protein_id, source_db)InterProProtein domains, families, structural info
search_interpro(query, entry_type)InterProDomain search by keyword
query_string(protein_symbol, species, min_score)STRINGProtein-protein interactions
query_hpa(gene_symbol)Human Protein AtlasTissue expression, subcellular localization

Pathways & Functional

FunctionDatabaseReturns
query_reactome(identifier, species)ReactomePathway membership, reactions, disease links
query_go(gene_name, size)Gene OntologyGO term associations (BP, MF, CC)

Cell Biology

FunctionDatabaseReturns
query_panglaodb(species, cell_type, organ)PanglaoDBCell type marker genes with sensitivity/specificity

Literature

FunctionDatabaseReturns
search_literature(query, sort_by, page_size)Europe PMCPublications matching keywords
search_preprints(server, days, category)bioRxiv/medRxivRecent preprints
get_fulltext(pmc_id)PubMed CentralFull-text article content

Drug & Clinical

FunctionDatabaseReturns
query_opentargets(query_string, variables)OpenTargetsGene-disease-drug associations
search_clinical_trials(condition, status)ClinicalTrials.govActive/completed trials
search_drugs(brand_name, generic_name)openFDADrug information, approval status

Ontology

FunctionDatabaseReturns
query_efo(disease_name, size, exact_match)EFOExperimental Factor Ontology terms
query_chebi(chemical_name, size)ChEBIChemical entities, small molecules
query_cell_ontology(cell_type, size)Cell OntologyStandardized cell type hierarchy

Proteomics

FunctionDatabaseReturns
search_pride(keyword, page_size)PRIDEMass spectrometry proteomics datasets

Generic Access

# List all 49 available tools with parameters
ov.biocontext.list_tools()

# Call any tool directly by name
result = ov.biocontext.call_tool("tool_name", param1=value1, ...)

Usage Patterns

Single gene lookup

import omicverse as ov

# Get protein function and domains
info = ov.biocontext.query_uniprot(gene_symbol='TP53', species='9606')

# Get pathway membership
pathways = ov.biocontext.query_reactome(identifier='TP53', species='Homo sapiens')

# Get GO terms
go_terms = ov.biocontext.query_go(gene_name='TP53', size=20)

Annotate a DEG list

# After differential expression: annotate top genes with biological context
deg_genes = ['TP53', 'BRCA1', 'MYC', 'EGFR', 'KRAS']
annotations = {}
for gene in deg_genes:
    annotations[gene] = {
        'uniprot': ov.biocontext.query_uniprot(gene_symbol=gene),
        'pathways': ov.biocontext.query_reactome(identifier=gene),
        'go': ov.biocontext.query_go(gene_name=gene, size=5),
    }

Find cell type markers

# Get known markers for a cell type
markers = ov.biocontext.query_panglaodb(
    species='Hs',           # 'Hs' (human), 'Mm' (mouse), 'Dr' (zebrafish)
    cell_type='T cells',
    organ='Blood',
    min_sensitivity=0.5,
)
# Returns: DataFrame with gene symbols, sensitivity, specificity scores

Drug target exploration

# Find drugs targeting a gene
targets = ov.biocontext.query_opentargets(
    query_string='{ target(ensemblId: "ENSG00000141510") { associatedDiseases { rows { disease { name } score } } } }'
)

# Search clinical trials
trials = ov.biocontext.search_clinical_trials(condition='breast cancer', status='RECRUITING')

Literature search

# Search for papers
results = ov.biocontext.search_literature(
    query='single-cell RNA-seq BRCA1',
    sort_by='RELEVANCE',
    page_size=5,
)

# Get full text of a specific paper
text = ov.biocontext.get_fulltext(pmc_id='PMC1234567')

Species Codes

Different databases use different species identifiers:

SpeciesNCBI Taxon IDEnsemblPanglaoDB
Human9606homo_sapiensHs
Mouse10090mus_musculusMm
Zebrafish7955danio_rerioDr
Rat10116rattus_norvegicusRn

Most functions default to human (9606 or homo_sapiens).

Critical API Reference

query_uniprot accepts multiple identifier types

# By gene symbol (most common)
ov.biocontext.query_uniprot(gene_symbol='TP53')

# By UniProt accession
ov.biocontext.query_uniprot(protein_id='P04637')

# By protein name
ov.biocontext.query_uniprot(protein_name='Cellular tumor antigen p53')

query_opentargets uses GraphQL

# OpenTargets requires GraphQL query strings
# See OpenTargets Platform API docs for query syntax
result = ov.biocontext.query_opentargets(
    query_string='{ search(queryString: "BRCA1") { total hits { id name } } }'
)

Troubleshooting

  • Empty results for a known gene: Check species parameter. Default is human (9606) — pass species='10090' for mouse genes.
  • Timeout on large queries: External API calls have network latency. For batch annotation, add small delays between calls to avoid rate limiting.
  • ConnectionError: Requires internet access. BioContext queries external databases in real-time.
  • Gene symbol not found: Some databases are case-sensitive. Human genes should be uppercase (TP53), mouse mixed-case (Tp53).
  • OpenTargets query fails: GraphQL syntax must be exact. Use ov.biocontext.list_tools() to see available OpenTargets tool variants with example queries.

Examples

  • "Look up the protein function and pathways for my top 10 DEGs."
  • "Find known T-cell markers from PanglaoDB for my annotation."
  • "Search for recent papers about spatial transcriptomics and BRCA1."
  • "What drugs target EGFR? Check clinical trials status."

References