Claude-skill-registry bio-entrez-link
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.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/entrez-link" ~/.claude/skills/majiayu000-claude-skill-registry-bio-entrez-link && rm -rf "$T"
manifest:
skills/data/entrez-link/SKILL.mdsource content
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 |
|---|---|---|
| Source database | |
| Target database | |
| Source record ID(s) | or |
| Specific link type | |
| Link command | , |
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 | | All proteins |
| gene | protein | | RefSeq proteins only |
| gene | nucleotide | | Nucleotide sequences |
| gene | nucleotide | | RefSeq mRNA |
| gene | pubmed | | Related publications |
| gene | homologene | | Homologs |
| gene | snp | | SNPs in gene |
| gene | clinvar | | Clinical variants |
Nucleotide to Other Databases
| From | To | Link Name | Description |
|---|---|---|---|
| nucleotide | protein | | Encoded proteins |
| nucleotide | gene | | Gene records |
| nucleotide | pubmed | | Publications |
| nucleotide | taxonomy | | Organism taxonomy |
| nucleotide | biosample | | Sample info |
| nucleotide | sra | | Related SRA data |
Protein to Other Databases
| From | To | Link Name | Description |
|---|---|---|---|
| protein | nucleotide | | Coding sequences |
| protein | gene | | Gene records |
| protein | pubmed | | Publications |
| protein | structure | | 3D structures |
| protein | cdd | | Conserved domains |
PubMed Links
| From | To | Link Name | Description |
|---|---|---|---|
| pubmed | pubmed | | Related articles |
| pubmed | gene | | Mentioned genes |
| pubmed | protein | | Mentioned proteins |
| pubmed | nucleotide | | 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 |
|---|---|
| Default - get linked records |
| Include relevance scores |
| Store results in history |
| List all available links |
| Check if any links exist |
| Check specific link exists |
| Get URLs to Entrez links |
| Get provider links (external) |
Common Errors
| Error | Cause | Solution |
|---|---|---|
Empty | No links exist | Check if record has linked data |
| Invalid ID or database | Verify ID exists in source database |
| Missing expected field | Check if 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