# Biology Biopython

Bioinformatics with Biopython for sequence manipulation, file parsing, BLAST, and...

- Repository: https://github.com/aiming-lab/AutoResearchClaw (14798 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-08-19
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add aiming-lab/AutoResearchClaw --skill biology-biopython -g -a claude-code -y`
Codex: `npx skills add aiming-lab/AutoResearchClaw --skill biology-biopython -g -a codex -y`
Cursor: `npx skills add aiming-lab/AutoResearchClaw --skill biology-biopython -g -a cursor -y`
Gemini CLI: `npx skills add aiming-lab/AutoResearchClaw --skill biology-biopython -g -a gemini-cli -y`

## Description

Bioinformatics with Biopython for sequence manipulation, file parsing, BLAST, and phylogenetics. Use when working with DNA/RNA/protein sequences or biological databases.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## Biopython Bioinformatics Best Practice

### Sequence Manipulation
1. Create sequences: `from Bio.Seq import Seq; seq = Seq("ATGCGA")`
2. Complement: `seq.complement()`; Reverse complement: `seq.reverse_complement()`
3. Transcription: `seq.transcribe()` (DNA to RNA)
4. Translation: `seq.translate()` (DNA/RNA to protein)
5. GC content: `from Bio.SeqUtils import gc_fraction; gc_fraction(seq)`
6. Molecular weight: `from Bio.SeqUtils import molecular_weight`

### File Parsing (SeqIO)
1. Read FASTA: `for rec in SeqIO.parse("file.fasta", "fasta"): ...`
2. Read GenBank: `for rec in SeqIO.parse("file.gb", "genbank"): ...`
3. Read single record: `rec = SeqIO.read("file.fasta", "fasta")`
4. Write sequences: `SeqIO.write(records, "output.fasta", "fasta")`
5. Convert formats: `SeqIO.convert("input.gb", "genbank", "output.fasta", "fasta")`
6. Index large files: `idx = SeqIO.index("large.fasta", "fasta")` for random access

### BLAST Operations
1. Online BLAST: `from Bio.Blast import NCBIWWW; result = NCBIWWW.qblast("blastn", "nt", seq)`
2. Parse results: `from Bio.Blast import NCBIXML; records = NCBIXML.parse(result)`
3. Local BLAST: run via subprocess, parse XML output with NCBIXML
4. Always set `Entrez.email` before any NCBI access
5. Filter results by e-value (typically < 1e-5) and coverage

### NCBI Database Access (Entrez)
1. Always set email: `Entrez.email = "your@email.com"`
2. Search: `handle = Entrez.esearch(db="pubmed", term="query")`
3. Fetch records: `handle = Entrez.efetch(db="nucleotide", id="ID", rettype="fasta")`
4. Use API key for higher rate limits (10 req/s vs 3 req/s)
5. Respect NCBI rate limits; add delays between batch requests

The rest: https://github.com/aiming-lab/AutoResearchClaw/blob/HEAD/.claude/skills/biology-biopython/SKILL.md