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bio-entrez-link

bio-entrez-link，来自 FreedomIntelligence/OpenClaw-Medical-Skills 的 agent 技能。

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技能内容

<!--

COPYRIGHT NOTICE

This file is part of the "Universal Biomedical Skills" project.

Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>

All Rights Reserved.

#

This code is proprietary and confidential.

Unauthorized copying of this file, via any medium is strictly prohibited.

#

Provenance: Authenticated by MD BABU MIA

-->

name: bio-entrez-link

description: Find cross-references between NCBI databases using Biopython Bio.Entrez. Use when navigating from genes to proteins, sequences to publications, finding related records, or discovering database relationships.

tool_type: python

primary_tool: Bio.Entrez

measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.

allowed-tools:

  • read_file
  • run_shell_command

Entrez Link

Navigate between NCBI databases using Biopython's Entrez module (ELink utility).

Required Setup

from Bio import Entrez

Entrez.email = 'your.email@example.com'  # Required by NCBI
Entrez.api_key = 'your_api_key'          # Optional, raises rate limit

Core Function

Entrez.elink() - Cross-Database Links

Find related records in the same or different databases.

# Find proteins linked to a gene
handle = Entrez.elink(dbfrom='gene', db='protein', id='672')
record = Entrez.read(handle)
handle.close()

# Extract linked IDs
linkset = record[0]
if linkset['LinkSetDb']:
    links = linkset['LinkSetDb'][0]['Link']
    protein_ids = [link['Id'] for link in links]
    print(f"Found {len(protein_ids)} linked proteins")

Key Parameters:

| Parameter | Description | Example |

|-----------|-------------|---------|

| dbfrom | Source database | 'gene' |

| db | Target database | 'protein' |

| id | Source record ID(s) | '672' or '672,675' |

| linkname | Specific link type | 'gene_protein_refseq' |

| cmd | Link command | 'neighbor', 'neighbor_score' |

ELink Result Structure

record[0]                          # First linkset
record[0]['DbFrom']                # Source database
record[0]['IdList']                # Input IDs
record[0]['LinkSetDb']             # List of link results
record[0]['LinkSetDb'][0]['DbTo']  # Target database
record[0]['LinkSetDb'][0]['LinkName']  # Link name
record[0]['LinkSetDb'][0]['Link']  # List of linked records
record[0]['LinkSetDb'][0]['Link'][0]['Id']  # Linked ID

Common Link Paths

Gene to Other Databases

| From | To | Link Name | Description |

|------|-----|-----------|-------------|

| gene | protein | gene_protein | All proteins |

| gene | protein | gene_protein_refseq | RefSeq proteins only |

| gene | nucleotide | gene_nuccore | Nucleotide sequences |

| gene | nucleotide | gene_nuccore_refseqrna | RefSeq mRNA |

| gene | pubmed | gene_pubmed | Related publications |

| gene | homologene | gene_homologene | Homologs |

| gene | snp | gene_snp | SNPs in gene |

| gene | clinvar | gene_clinvar | Clinical variants |

Nucleotide to Other Databases

| From | To | Link Name | Description |

|------|-----|-----------|-------------|

| nucleotide | protein | nuccore_protein | Encoded proteins |

| nucleotide | gene | nuccore_gene | Gene records |

| nucleotide | pubmed | nuccore_pubmed | Publications |

| nucleotide | taxonomy | nuccore_taxonomy | Organism taxonomy |

| nucleotide | biosample | nuccore_biosample | Sample info |

| nucleotide | sra | nuccore_sra | Related SRA data |

Protein to Other Databases

| From | To | Link Name | Description |

|------|-----|-----------|-------------|

| protein | nucleotide | protein_nuccore | Coding sequences |

| protein | gene | protein_gene | Gene records |

| protein | pubmed | protein_pubmed | Publications |

| protein | structure | protein_structure | 3D structures |

| protein | cdd | protein_cdd | Conserved domains |

PubMed Links

| From | To | Link Name | Description |

|------|-----|-----------|-------------|

| pubmed | pubmed | pubmed_pubmed | Related articles |

| pubmed | gene | pubmed_gene | Mentioned genes |

| pubmed | protein | pubmed_protein | Mentioned proteins |

| pubmed | nucleotide | pubmed_nuccore | Mentioned sequences |

Code Patterns

Gene to Protein

from Bio import Entrez

Entrez.email = 'your.email@example.com'

def get_proteins_for_gene(gene_id):
    handle = Entrez.elink(dbfrom='gene', db='protein', id=gene_id, linkname='gene_protein_refseq')
    record = Entrez.read(handle)
    handle.close()

    if not record[0]['LinkSetDb']:
        return []
    return [link['Id'] for link in record[0]['LinkSetDb'][0]['Link']]

protein_ids = get_proteins_for_gene('672')  # BRCA1
print(f"RefSeq proteins: {protein_ids[:5]}")

Nucleotide to Gene

def get_gene_for_nucleotide(nuc_id):
    handle = Entrez.elink(dbfrom='nucleotide', db='gene', id=nuc_id)
    record = Entrez.read(handle)
    handle.close()

    if not record[0]['LinkSetDb']:
        return None
    return record[0]['LinkSetDb'][0]['Link'][0]['Id']

gene_id = get_gene_for_nucleotide('NM_007294')
print(f"Gene ID: {gene_id}")

Find Related PubMed Articles

def get_related_articles(pmid, max_results=10):
    handle = Entrez.elink(dbfrom='pubmed', db='pubmed', id=pmid, linkname='pubmed_pubmed')
    record = Entrez.read(handle)
    handle.close()

    if not record[0]['LinkSetDb']:
        return []
    links = record[0]['LinkSetDb'][0]['Link']
    return [link['Id'] for link in links[:max_results]]

related = get_related_articles('35412348')
print(f"Related articles: {related}")

Get All Available Links

def discover_links(db, record_id):
    handle = Entrez.elink(dbfrom=db, id=record_id, cmd='acheck')
    record = Entrez.read(handle)
    handle.close()

    links = {}
    for linkset in record[0].get('LinkSetDb', []):
        links[linkset['LinkName']] = linkset['DbTo']
    return links

available = discover_links('gene', '672')
for name, target in available.items():
    print(f"{name} -> {target}")

Navigate Gene -> Protein -> Structure

def gene_to_structures(gene_id):
    # Gene to protein
    handle = Entrez.elink(dbfrom='gene', db='protein', id=gene_id, linkname='gene_protein_refseq')
    record = Entrez.read(handle)
    handle.close()

    if not record[0]['LinkSetDb']:
        return []
    protein_ids = [link['Id'] for link in record[0]['LinkSetDb'][0]['Link'][:5]]

    # Protein to structure
    handle = Entrez.elink(dbfrom='protein', db='structure', id=','.join(protein_ids))
    record = Entrez.read(handle)
    handle.close()

    structure_ids = []
    for linkset in record:
        if linkset['LinkSetDb']:
            structure_ids.extend([link['Id'] for link in linkset['LinkSetDb'][0]['Link']])
    return structure_ids

structures = gene_to_structures('672')
print(f"Structure IDs: {structures[:5]}")

Link Multiple IDs at Once

def batch_link(dbfrom, db, ids):
    if isinstance(ids, list):
        ids = ','.join(ids)

    handle = Entrez.elink(dbfrom=dbfrom, db=db, id=ids)
    record = Entrez.read(handle)
    handle.close()

    # Returns one linkset per input ID
    results = {}
    for linkset in record:
        source_id = linkset['IdList'][0]
        linked_ids = []
        if linkset['LinkSetDb']:
            linked_ids = [link['Id'] for link in linkset['LinkSetDb'][0]['Link']]
        results[source_id] = linked_ids
    return results

results = batch_link('gene', 'protein', ['672', '675', '7157'])
for gene, proteins in results.items():
    print(f"Gene {gene}: {len(proteins)} proteins")

Get Publications for a Sequence

def get_sequence_publications(accession):
    # First get the GI/UID
    handle = Entrez.esearch(db='nucleotide', term=f'{accession}[accn]')
    search = Entrez.read(handle)
    handle.close()

    if not search['IdList']:
        return []
    uid = search['IdList'][0]

    # Link to PubMed
    handle = Entrez.elink(dbfrom='nucleotide', db='pubmed', id=uid)
    record = Entrez.read(handle)
    handle.close()

    if not record[0]['LinkSetDb']:
        return []
    return [link['Id'] for link in record[0]['LinkSetDb'][0]['Link']]

pmids = get_sequence_publications('NM_007294')
print(f"PubMed IDs: {pmids[:5]}")

Link Commands

| Command | Description |

|---------|-------------|

| neighbor | Default - get linked records |

| neighbor_score | Include relevance scores |

| neighbor_history | Store results in history |

| acheck | List all available links |

| ncheck | Check if any links exist |

| lcheck | Check specific link exists |

| llinks | Get URLs to Entrez links |

| prlinks | Get provider links (external) |

Common Errors

| Error | Cause | Solution |

|-------|-------|----------|

| Empty LinkSetDb | No links exist | Check if record has linked data |

| HTTPError 400 | Invalid ID or database | Verify ID exists in source database |

| KeyError | Missing expected field | Check if LinkSetDb is empty first |

| Single linkset expected, got list | Multiple input IDs | Iterate through record list |

Decision Tree

Need to find related records?
├── Know what link you want?
│   └── Use elink with specific linkname
├── Discover what links exist?
│   └── Use elink with cmd='acheck'
├── Navigate to target database?
│   └── Use elink(dbfrom=X, db=Y, id=Z)
├── Find related records in same database?
│   └── Use elink(dbfrom=X, db=X) with neighbor
├── Chain multiple databases?
│   └── Call elink multiple times
└── Need the actual records?
    └── Use elink first, then efetch with IDs

Related Skills

  • entrez-search - Search databases before linking
  • entrez-fetch - Retrieve records after finding linked IDs
  • batch-downloads - Download many linked records efficiently

<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

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仓库FreedomIntelligence/OpenClaw-Medical-Skills
星标★ 3,010
本站分层T1
该仓技能数897
原文件路径skills/bio-entrez-link/SKILL.md

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