菜单
Search PubMed for scientific literature. Use when the user asks to find papers, search literature, look up research, find publications, or asks about recent studies. Triggers on "pubmed", "papers", "literature", "publications", "research on", "studies about".
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Run BLAST sequence similarity searches. Use when the user asks to BLAST a sequence, find similar sequences, identify a gene/protein, or do homology search. Triggers on "blast", "sequence similarity", "homology", "identify sequence".
Query AlphaFold protein structure predictions. Use when user asks about protein structure, 3D structure, protein folding, or structure prediction. Triggers on "alphafold", "protein structure", "3D structure", "folding", "pLDDT", "structure prediction".
Query ClinVar for clinical variant significance. Use when user asks about variant pathogenicity, genetic variants, clinical significance, or disease-causing mutations. Triggers on "clinvar", "pathogenic", "variant significance", "clinical significance", "disease variant", "mutation pathogenicity".
Query NCBI GEO for gene expression datasets. Use when user asks about RNA-seq datasets, microarray data, expression data, GEO accessions, or finding public datasets. Triggers on "geo", "gene expression omnibus", "expression dataset", "RNA-seq dataset", "microarray dataset", "GSE", "GDS".
Query STRING for protein-protein interactions. Use when user asks about protein interactions, interaction networks, binding partners, or interactome. Triggers on "string", "protein interaction", "interaction network", "binding partners", "interactome", "PPI".
| name | pubmed-search |
| description | Search PubMed for scientific literature. Use when the user asks to find papers, search literature, look up research, find publications, or asks about recent studies. Triggers on "pubmed", "papers", "literature", "publications", "research on", "studies about". |
Search NCBI PubMed for scientific literature using BioPython's Entrez module.
from Bio import Entrez
Entrez.email = "bioclaw@example.com"
# Search
handle = Entrez.esearch(db="pubmed", term="CRISPR delivery methods", retmax=20, sort="date")
record = Entrez.read(handle)
handle.close()
id_list = record["IdList"]
print(f"Found {record['Count']} results, showing top {len(id_list)}")
# Fetch details
handle = Entrez.efetch(db="pubmed", id=id_list, rettype="xml")
records = Entrez.read(handle)
handle.close()
for article in records['PubmedArticle']:
medline = article['MedlineCitation']
pmid = str(medline['PMID'])
title = medline['Article']['ArticleTitle']
# Get authors
authors = medline['Article'].get('AuthorList', [])
first_author = f"{authors[0].get('LastName', '')} {authors[0].get('Initials', '')}" if authors else "Unknown"
# Get journal and year
journal = medline['Article']['Journal']['Title']
pub_date = medline['Article']['Journal']['JournalIssue'].get('PubDate', {})
year = pub_date.get('Year', 'N/A')
# Get abstract
abstract_parts = medline['Article'].get('Abstract', {}).get('AbstractText', [])
abstract = ' '.join(str(a) for a in abstract_parts)[:300]
print(f"PMID: {pmid}")
print(f"Title: {title}")
print(f"Authors: {first_author} et al.")
print(f"Journal: {journal} ({year})")
print(f"Abstract: {abstract}...")
print(f"Link: https://pubmed.ncbi.nlm.nih.gov/{pmid}/")
print()
*PubMed Search: "CRISPR delivery methods"*
_Found 1,234 results. Top 5:_
*1.* Lipid nanoparticle-mediated CRISPR delivery...
_Smith J et al. — Nature (2026)_
PMID: 12345678
pubmed.ncbi.nlm.nih.gov/12345678
*2.* AAV-based CRISPR therapeutics: advances and challenges
_Chen L et al. — Cell (2026)_
PMID: 12345679
pubmed.ncbi.nlm.nih.gov/12345679
Support these query patterns:
"CRISPR"[Title] AND "delivery"[Title] — title-specific"2026"[Date - Publication] — date filter"Nature"[Journal] — journal filterreview[Publication Type] — type filterAfter showing results, suggest: