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GPTomics

bio-entrez-search

by GPTomics

a set of SKILLS.md for doing bioinformatics with agents like claude code

65🍴 17📅 2026年1月24日
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name: bio-entrez-search description: Search NCBI databases using Biopython Bio.Entrez. Use when finding records by keyword, building complex search queries, discovering database structure, or getting global query counts across databases. tool_type: python primary_tool: Bio.Entrez

Entrez Search

Search NCBI databases using Biopython's Entrez module (ESearch, EInfo, EGQuery utilities).

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 3->10 req/sec

Core Functions

Entrez.esearch() - Search a Database

Search any NCBI database and get matching record IDs.

handle = Entrez.esearch(db='nucleotide', term='human[orgn] AND BRCA1[gene]')
record = Entrez.read(handle)
handle.close()

print(f"Found {record['Count']} records")
print(f"IDs: {record['IdList']}")  # First 20 IDs by default

Key Parameters:

ParameterDescriptionDefault
dbDatabase to searchRequired
termSearch queryRequired
retmaxMax IDs to return20
retstartStarting index (pagination)0
usehistoryStore results on server'n'
sortSort orderdatabase-specific
datetypeDate field to search'pdat'
reldateRecords from last N daysNone
mindateStart date (YYYY/MM/DD)None
maxdateEnd date (YYYY/MM/DD)None

ESearch Result Fields:

record['Count']        # Total matching records (string)
record['IdList']       # List of record IDs
record['RetMax']       # Number of IDs returned
record['RetStart']     # Starting index
record['QueryKey']     # For history server (if usehistory='y')
record['WebEnv']       # For history server (if usehistory='y')
record['TranslationSet']  # Query translations applied
record['QueryTranslation']  # Final translated query

Entrez.einfo() - Database Information

Get information about available databases or specific database fields.

# List all available databases
handle = Entrez.einfo()
record = Entrez.read(handle)
handle.close()
print(record['DbList'])  # ['pubmed', 'protein', 'nucleotide', ...]

# Get info about specific database
handle = Entrez.einfo(db='nucleotide')
record = Entrez.read(handle)
handle.close()

print(f"Description: {record['DbInfo']['Description']}")
print(f"Record count: {record['DbInfo']['Count']}")

# List searchable fields
for field in record['DbInfo']['FieldList']:
    print(f"{field['Name']}: {field['Description']}")

Database Info Fields:

record['DbInfo']['DbName']       # Database name
record['DbInfo']['Description']  # Database description
record['DbInfo']['Count']        # Total records in database
record['DbInfo']['LastUpdate']   # Last update date
record['DbInfo']['FieldList']    # Searchable fields
record['DbInfo']['LinkList']     # Available links to other databases

Entrez.egquery() - Global Query

Search across all NCBI databases simultaneously.

handle = Entrez.egquery(term='CRISPR')
record = Entrez.read(handle)
handle.close()

for result in record['eGQueryResult']:
    if int(result['Count']) > 0:
        print(f"{result['DbName']}: {result['Count']} records")

Search Query Syntax

NCBI uses a specific query syntax:

Field Tags

# Search specific fields using [field_name]
term = 'BRCA1[gene]'                    # Gene name field
term = 'human[orgn]'                    # Organism field
term = 'Homo sapiens[ORGN]'             # Full organism name
term = 'NM_007294[accn]'                # Accession number
term = 'Smith J[auth]'                  # Author (PubMed)
term = 'Nature[jour]'                   # Journal (PubMed)
term = '1000:5000[slen]'                # Sequence length range
term = 'mRNA[fkey]'                     # Feature key

Boolean Operators

term = 'BRCA1 AND human'                # Both terms
term = 'cancer OR tumor'                # Either term
term = 'human NOT mouse'                # Exclude term
term = '(BRCA1 OR BRCA2) AND human'     # Grouping

Date Ranges

# Using date parameters
handle = Entrez.esearch(
    db='pubmed',
    term='CRISPR',
    datetype='pdat',     # Publication date
    mindate='2023/01/01',
    maxdate='2024/12/31'
)

# Or in query string
term = 'CRISPR AND 2024[pdat]'
term = 'CRISPR AND 2023:2024[pdat]'

Wildcards and Phrases

term = 'immun*'                         # Wildcard
term = '"breast cancer"[title]'         # Exact phrase

Common Databases

Databasedb valueCommon Fields
PubMedpubmed[auth], [title], [jour], [pdat]
Nucleotidenucleotide[orgn], [gene], [accn], [slen]
Proteinprotein[orgn], [gene], [accn], [molwt]
Genegene[orgn], [sym], [chr]
SRAsra[orgn], [platform], [strategy]
Taxonomytaxonomy[scin], [comn], [rank]
Assemblyassembly[orgn], [level], [refseq]

Code Patterns

Basic Search with Pagination

from Bio import Entrez

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

def search_ncbi(db, term, max_results=100):
    handle = Entrez.esearch(db=db, term=term, retmax=max_results)
    record = Entrez.read(handle)
    handle.close()
    return record['IdList'], int(record['Count'])

ids, total = search_ncbi('nucleotide', 'human[orgn] AND insulin[gene]')
print(f'Retrieved {len(ids)} of {total} total records')

Paginated Search for Large Results

def search_all_ids(db, term, batch_size=10000):
    all_ids = []
    handle = Entrez.esearch(db=db, term=term, retmax=0)
    record = Entrez.read(handle)
    handle.close()
    total = int(record['Count'])

    for start in range(0, total, batch_size):
        handle = Entrez.esearch(db=db, term=term, retstart=start, retmax=batch_size)
        record = Entrez.read(handle)
        handle.close()
        all_ids.extend(record['IdList'])

    return all_ids

Search with History Server (for Large Results)

# Store results on NCBI server for subsequent fetching
handle = Entrez.esearch(db='nucleotide', term='human[orgn] AND mRNA[fkey]', usehistory='y')
record = Entrez.read(handle)
handle.close()

webenv = record['WebEnv']
query_key = record['QueryKey']
total = int(record['Count'])

# Use webenv and query_key with efetch for batch downloads
# See batch-downloads skill for details

Recent Records Only

# Records from last 30 days
handle = Entrez.esearch(db='pubmed', term='CRISPR', reldate=30, datetype='pdat')
record = Entrez.read(handle)
handle.close()

Get Available Fields for a Database

def get_search_fields(db):
    handle = Entrez.einfo(db=db)
    record = Entrez.read(handle)
    handle.close()
    return [(f['Name'], f['Description']) for f in record['DbInfo']['FieldList']]

fields = get_search_fields('nucleotide')
for name, desc in fields[:10]:
    print(f'{name}: {desc}')

Check Query Translation

handle = Entrez.esearch(db='nucleotide', term='human BRCA1')
record = Entrez.read(handle)
handle.close()

# See how NCBI interpreted your query
print(f"Your query was translated to: {record['QueryTranslation']}")
# e.g., '"homo sapiens"[Organism] AND BRCA1[All Fields]'

Common Errors

ErrorCauseSolution
HTTPError 429Rate limit exceededAdd delays or use API key
HTTPError 400Invalid query syntaxCheck field names and operators
Empty IdListNo matches or typoCheck QueryTranslation field
RuntimeErrorMissing emailSet Entrez.email

Decision Tree

Need to search NCBI?
├── Finding records in one database?
│   └── Use Entrez.esearch()
├── Search across all databases?
│   └── Use Entrez.egquery()
├── Need database field names?
│   └── Use Entrez.einfo(db='database')
├── List all available databases?
│   └── Use Entrez.einfo() (no db argument)
├── Results > 10,000 records?
│   └── Use usehistory='y', then batch fetch
└── Need to fetch actual records?
    └── See entrez-fetch skill
  • entrez-fetch - Retrieve full records after searching
  • entrez-link - Find related records in other databases
  • batch-downloads - Download large result sets efficiently
  • geo-data - Search GEO expression datasets (specialized search)
  • blast-searches - Search by sequence similarity instead of keywords

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