Agent Skills
› aiming-lab/AutoResearchClaw
› biology-biopython
biology-biopython
GitHub提供Biopython生物信息学最佳实践，涵盖序列操作、文件解析、BLAST分析、NCBI数据库访问及系统发育和结构分析。
Trigger Scenarios
处理DNA/RNA/蛋白质序列
生物信息学数据分析
解析FASTA或GenBank文件
进行BLAST比对
访问NCBI数据库
Install
npx skills add aiming-lab/AutoResearchClaw --skill biology-biopython -g -y
SKILL.md
Frontmatter
{
"name": "biology-biopython",
"metadata": {
"author": "researchclaw",
"version": "1.0",
"category": "domain",
"priority": "4",
"references": "adapted from K-Dense-AI\/claude-scientific-skills",
"trigger-keywords": "sequence,FASTA,genome,protein,BLAST,phylogenetic,biopython,bioinformatics,gene,DNA,RNA",
"applicable-stages": "9,10,12"
},
"description": "Bioinformatics with Biopython for sequence manipulation, file parsing, BLAST, and phylogenetics. Use when working with DNA\/RNA\/protein sequences or biological databases."
}
Biopython Bioinformatics Best Practice
Sequence Manipulation
- Create sequences:
from Bio.Seq import Seq; seq = Seq("ATGCGA") - Complement:
seq.complement(); Reverse complement:seq.reverse_complement() - Transcription:
seq.transcribe()(DNA to RNA) - Translation:
seq.translate()(DNA/RNA to protein) - GC content:
from Bio.SeqUtils import gc_fraction; gc_fraction(seq) - Molecular weight:
from Bio.SeqUtils import molecular_weight
File Parsing (SeqIO)
- Read FASTA:
for rec in SeqIO.parse("file.fasta", "fasta"): ... - Read GenBank:
for rec in SeqIO.parse("file.gb", "genbank"): ... - Read single record:
rec = SeqIO.read("file.fasta", "fasta") - Write sequences:
SeqIO.write(records, "output.fasta", "fasta") - Convert formats:
SeqIO.convert("input.gb", "genbank", "output.fasta", "fasta") - Index large files:
idx = SeqIO.index("large.fasta", "fasta")for random access
BLAST Operations
- Online BLAST:
from Bio.Blast import NCBIWWW; result = NCBIWWW.qblast("blastn", "nt", seq) - Parse results:
from Bio.Blast import NCBIXML; records = NCBIXML.parse(result) - Local BLAST: run via subprocess, parse XML output with NCBIXML
- Always set
Entrez.emailbefore any NCBI access - Filter results by e-value (typically < 1e-5) and coverage
NCBI Database Access (Entrez)
- Always set email:
Entrez.email = "your@email.com" - Search:
handle = Entrez.esearch(db="pubmed", term="query") - Fetch records:
handle = Entrez.efetch(db="nucleotide", id="ID", rettype="fasta") - Use API key for higher rate limits (10 req/s vs 3 req/s)
- Respect NCBI rate limits; add delays between batch requests
Phylogenetics (Bio.Phylo)
- Read trees:
from Bio import Phylo; tree = Phylo.read("tree.nwk", "newick") - Draw trees:
Phylo.draw(tree)orPhylo.draw_ascii(tree) - Supported formats: newick, nexus, phyloxml
- Traverse clades:
for clade in tree.find_clades(): ... - Calculate distances:
tree.distance(clade1, clade2)
Structure Analysis (Bio.PDB)
- Parse PDB:
parser = PDBParser(); structure = parser.get_structure("id", "file.pdb") - Hierarchy: Structure > Model > Chain > Residue > Atom
- Get atoms: iterate through
structure.get_atoms() - Calculate distances: use atom coordinate vectors
- For mmCIF files: use
MMCIFParser()instead ofPDBParser()
Common Pitfalls
- Always handle
SeqIO.parseas an iterator — it exhausts after one pass - Check sequence alphabet compatibility before operations
- Large files: use
SeqIO.index()notSeqIO.to_dict()to avoid memory issues - Set proper timeout for remote BLAST queries (can take minutes)
- Validate parsed data — missing annotations are common in public databases
Version History
- e2e23c9 Current 2026-07-25 07:47
