biopython（BioPython 生物信息）

Biopython: Python Tools for Computational Biology

Summary

Biopython (v1.85+) delivers a comprehensive Python library for biological data analysis. It requires Python 3 and NumPy, providing modular components for sequences, alignments, database access, BLAST, structures, and phylogenetics.

Applicable Scenarios

This skill applies when you need to:

Module Organization

Setup

Install via pip:

uv pip install biopython

Configure NCBI access (mandatory for Entrez operations):

from Bio import Entrez

Entrez.email = "researcher@institution.edu"
Entrez.api_key = "your_ncbi_api_key"  # Optional: increases rate limit to 10 req/s

Quick Reference

Parse Sequences

from Bio import SeqIO

records = SeqIO.parse("data.fasta", "fasta")
for rec in records:
    print(f"{rec.id}: {len(rec)} bp")

Translate DNA

from Bio.Seq import Seq

dna = Seq("ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG")
protein = dna.translate()

Query NCBI

from Bio import Entrez

Entrez.email = "researcher@institution.edu"
handle = Entrez.esearch(db="nucleotide", term="insulin[Gene] AND human[Organism]")
results = Entrez.read(handle)
handle.close()

Run BLAST

from Bio.Blast import NCBIWWW, NCBIXML

result = NCBIWWW.qblast("blastp", "swissprot", "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQAPILSRVGDGTQDNLSGAEKAVQVKVKALPDAQFEVVHSLAKWKRQQIAAALEHHHHHH")
record = NCBIXML.read(result)

Parse Protein Structure

from Bio.PDB import PDBParser

parser = PDBParser(QUIET=True)
structure = parser.get_structure("protein", "structure.pdb")
for atom in structure.get_atoms():
    print(atom.name, atom.coord)

Build Phylogenetic Tree

from Bio import AlignIO, Phylo
from Bio.Phylo.TreeConstruction import DistanceCalculator, DistanceTreeConstructor

alignment = AlignIO.read("aligned.fasta", "fasta")
calc = DistanceCalculator("identity")
dm = calc.get_distance(alignment)
tree = DistanceTreeConstructor().nj(dm)
Phylo.draw_ascii(tree)

Reference Files

Implementation Patterns

Retrieve and Analyze GenBank Record

from Bio import Entrez, SeqIO
from Bio.SeqUtils import gc_fraction

Entrez.email = "researcher@institution.edu"

handle = Entrez.efetch(db="nucleotide", id="NM_001301717", rettype="gb", retmode="text")
record = SeqIO.read(handle, "genbank")
handle.close()

print(f"Organism: {record.annotations['organism']}")
print(f"Length: {len(record)} bp")
print(f"GC: {gc_fraction(record.seq):.1%}")

Batch Sequence Processing

from Bio import SeqIO
from Bio.SeqUtils import gc_fraction

output_records = []
for record in SeqIO.parse("input.fasta", "fasta"):
    if len(record) >= 200 and gc_fraction(record.seq) > 0.4:
        output_records.append(record)

SeqIO.write(output_records, "filtered.fasta", "fasta")

BLAST with Result Filtering

from Bio.Blast import NCBIWWW, NCBIXML

query = "MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSH"
result_handle = NCBIWWW.qblast("blastp", "nr", query, hitlist_size=20)
record = NCBIXML.read(result_handle)

for alignment in record.alignments:
    for hsp in alignment.hsps:
        if hsp.expect < 1e-10:
            identity_pct = (hsp.identities / hsp.align_length) * 100
            print(f"{alignment.accession}: {identity_pct:.1f}% identity, E={hsp.expect:.2e}")

Phylogeny from Alignment

from Bio import AlignIO, Phylo
from Bio.Phylo.TreeConstruction import DistanceCalculator, DistanceTreeConstructor
import matplotlib.pyplot as plt

alignment = AlignIO.read("sequences.aln", "clustal")
calculator = DistanceCalculator("blosum62")
dm = calculator.get_distance(alignment)

constructor = DistanceTreeConstructor()
tree = constructor.nj(dm)
tree.root_at_midpoint()
tree.ladderize()

fig, ax = plt.subplots(figsize=(12, 8))
Phylo.draw(tree, axes=ax)
fig.savefig("phylogeny.png", dpi=150)

Guidelines

Imports: Use explicit imports

from Bio import SeqIO, Entrez
from Bio.Seq import Seq

File Handling: Always close handles or use context managers

with open("sequences.fasta") as f:
    for record in SeqIO.parse(f, "fasta"):
        process(record)

Memory Efficiency: Use iterators for large datasets

# Correct: iterate without loading all
for record in SeqIO.parse("huge.fasta", "fasta"):
    if meets_criteria(record):
        yield record

# Avoid: loading entire file
all_records = list(SeqIO.parse("huge.fasta", "fasta"))

Error Handling: Wrap network operations

from urllib.error import HTTPError

try:
    handle = Entrez.efetch(db="nucleotide", id=accession)
    record = SeqIO.read(handle, "genbank")
except HTTPError as e:
    print(f"Fetch failed: {e.code}")

NCBI Compliance: Set email, respect rate limits, cache downloads locally

Troubleshooting

External Resources

• Biopython Documentation: https://biopython.org/docs/latest/
• Biopython Tutorial: https://biopython.org/docs/latest/Tutorial/
• GitHub Repository: https://github.com/biopython/biopython