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kmaneesh

BioPython MCP Server

by kmaneesh

entrez_link

Find related records across NCBI databases like PubMed, GenBank, and ClinVar to discover connections between genes, proteins, articles, and sequences.

Instructions

Find related records across NCBI databases using ELink.

This tool discovers relationships between records in different databases, such as finding PubMed articles related to genes, or nucleotide sequences related to proteins.

Args: source_db: Source database (e.g., 'gene', 'protein', 'clinvar') target_db: Target database to link to (e.g., 'pubmed', 'nucleotide') ids: Single ID, comma-separated string, or list of IDs from source_db link_name: Specific link type (optional, empty = all available links)

Returns: Dictionary containing: - source_db: Source database name - target_db: Target database name - source_ids: List of source IDs queried - linked_ids: Dict mapping source IDs to lists of linked target IDs - total_links: Total number of links found - link_name: Link type used (if specified)

Examples: >>> entrez_link("gene", "pubmed", "672") # BRCA1 gene to PubMed >>> entrez_link("protein", "nucleotide", ["NP_000198.1", "NP_001121"]) >>> entrez_link("clinvar", "pubmed", "12345", link_name="clinvar_pubmed")

Notes: - Discovers cross-database relationships automatically - Use entrez_info() to see available link names for databases - Rate limited (3 req/sec or 10 req/sec with API key) - Different databases support different link types

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_dbYes
target_dbYes
idsYes
link_nameNo

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