biopython

name biopython description Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices. allowed-tools Read Write Edit Bash compatibility Requires Python 3.10+, NumPy, and Biopython. Entrez and web BLAST examples require network access; local BLAST/MUSCLE examples require those command-line tools installed separately. license Biopython License Agreement metadata {"version":"1.3","skill-author":"K-Dense Inc.","openclaw":{"envVars":["[Truncated]","[Truncated]"]}} Biopython: Computational Molecular Biology in Python Overview Biopython is a comprehensive set of freely available Python tools for biological computation. It provides functionality for sequence manipulation, file I/O, database access, structural bioinformatics, phylogenetics, and many other bioinformatics tasks. The current version is Biopython 1.87 (released 30 March 2026). It supports Python 3.10-3.14 and PyPy3.10, and requires NumPy. Biopython 1.87 also addresses CVE-2025-68463 in Bio.Entrez.Parser when parsing untrusted files, so prefer 1.87+ for workflows that parse externally supplied Entrez XML. When to Use This Skill Use this skill when: Working with biological sequences (DNA, RNA, or protein) Reading, writing, or converting biological file formats (FASTA, GenBank, FASTQ, PDB, mmCIF, etc.) Accessing NCBI databases (GenBank, PubMed, Protein, Gene, etc.) via Entrez Running BLAST searches or parsing BLAST results Performing sequence alignments (pairwise or multiple sequence alignments) Analyzing protein structures from PDB files Creating, manipulating, or visualizing phylogenetic trees Finding sequence motifs or analyzing motif patterns Calculating sequence statistics (GC content, molecular weight, melting temperature, etc.) Performing structural bioinformatics tasks Working with population genetics data Any other computational molecular biology task Core Capabilities Biopython is organized into modular sub-packages, each addressing specific bioinformatics domains: Sequence Handling - Bio.Seq and Bio.SeqIO for sequence manipulation and file I/O Alignment Analysis - Bio.Align and Bio.AlignIO for pairwise and multiple sequence alignments Database Access - Bio.Entrez for programmatic access to NCBI databases BLAST Operations - Bio.Blast for running and parsing BLAST searches Structural Bioinformatics - Bio.PDB for working with 3D protein structures Phylogenetics - Bio.Phylo for phylogenetic tree manipulation and visualization Advanced Features - Motifs, population genetics, sequence utilities, and more Installation and Setup Install the current stable Biopython release with an explicit version pin for reproducibility: uv pip install "biopython==1.87" For NCBI database access, always set your email address (required by NCBI). For reusable software, set a stable Entrez.tool value and register the tool/email with NCBI. For higher rate limits (10 req/s instead of 3 req/s), read only NCBI_API_KEY from the environment — do not hardcode keys or load unrelated environment variables: import os from Bio import Entrez Entrez.email = "your.email@example.com" # required — use your real email Entrez.tool = "your_tool_name" # optional but recommended for reusable software # Optional: register at https://www.ncbi.nlm.nih.gov/account/settings/ if api_key := os.environ.get( "NCBI_API_KEY" ): Entrez.api_key = api_key Using This Skill This skill provides comprehensive documentation organized by functionality area. When working on a task, consult the relevant reference documentation: 1. Sequence Handling (Bio.Seq & Bio.SeqIO) Reference: references/sequence_io.md Use for: Creating and manipulating biological sequences Reading and writing sequence files (FASTA, GenBank, FASTQ, etc.) Converting between file formats Extracting sequences from large files Sequence translation, transcription, and reverse complement Working with SeqRecord objects Quick example: from Bio import SeqIO # Read sequences from FASTA file for record in SeqIO.parse( "sequences.fasta" , "fasta" ): print ( f" {record. id } : { len (record.seq)} bp" ) # Convert GenBank to FASTA SeqIO.convert( "input.gb" , "genbank" , "output.fasta" , "fasta" ) 2. Alignment Analysis (Bio.Align & Bio.AlignIO) Reference: references/alignment.md Use for: Pairwise sequence alignment (global and local) Reading and writing multiple sequence alignments Using substitution matrices (BLOSUM, PAM) Calculating alignment statistics Customizing alignment parameters Quick example: from Bio import Align # Pairwise alignment aligner = Align.PairwiseAligner() aligner.mode = 'global' alignments = aligner.align( "ACCGGT" , "ACGGT" ) print (alignments[ 0 ]) 3. Database Access (Bio.Entrez) Reference: references/databases.md Use for: Searching NCBI databases (PubMed, GenBank, Protein, Gene, etc.) Downloading sequences and records Fetching publication information Finding related records across databases Batch downloading with proper rate limiting Quick example: from Bio import Entrez Entrez.email = "your.email@example.com" # Search PubMed handle = Entrez.esearch(db= "pubmed" , term= "biopython" , retmax= 10 ) results = Entrez.read(handle) handle.close() print ( f"Found {results[ 'Count' ]} results" ) 4. BLAST Operations (Bio.Blast) Reference: references/blast.md Use for: Running BLAST searches via NCBI web services Running local BLAST searches Parsing BLAST XML output Filtering results by E-value or identity Extracting hit sequences Quick example: from Bio.Blast import NCBIWWW, NCBIXML # Run BLAST search result_handle = NCBIWWW.qblast( "blastn" , "nt" , "ATCGATCGATCG" ) blast_record = NCBIXML.read(result_handle) # Display top hits for alignment in blast_record.alignments[: 5 ]: print ( f" {alignment.title} : E-value= {alignment.hsps[ 0 ].expect} " ) 5. Structural Bioinformatics (Bio.PDB) Reference: references/structure.md Use for: Parsing PDB and mmCIF structure files Navigating protein structure hierarchy (SMCRA: Structure/Model/Chain/Residue/Atom) Calculating distances, angles, and dihedrals Secondary structure assignment (DSSP) Structure superimposition and RMSD calculation Extracting sequences from structures Quick example: from Bio.PDB import PDBParser # Parse structure parser = PDBParser(QUIET= True ) structure = parser.get_structure( "1crn" , "1crn.pdb" ) # Calculate distance between alpha carbons chain = structure[ 0 ][ "A" ] distance = chain[ 10 ][ "CA" ] - chain[ 20 ][ "CA" ] print ( f"Distance: {distance: .2 f} Å" ) 6. Phylogenetics (Bio.Phylo) Reference: references/phylogenetics.md Use for: Reading and writing phylogenetic trees (Newick, NEXUS, phyloXML) Building trees from distance matrices or alignments Tree manipulation (pruning, rerooting, ladderizing) Calculating phylogenetic distances Creating consensus trees Visualizing trees Quick example: from Bio import Phylo # Read and visualize tree tree = Phylo.read( "tree.nwk" , "newick" ) Phylo.draw_ascii(tree) # Calculate distance distance = tree.distance( "Species_A" , "Species_B" ) print ( f"Distance: {distance: .3 f} " ) 7. Advanced Features Reference: references/advanced.md Use for: Sequence motifs (Bio.motifs) - Finding and analyzing motif patterns Population genetics (Bio.PopGen) - GenePop files, Fst calculations, Hardy-Weinberg tests Sequence utilities (Bio.SeqUtils) - GC content, melting temperature, molecular weight, protein analysis Restriction analysis (Bio.Restriction) - Finding restriction enzyme sites Clustering (Bio.Cluster) - K-means and hierarchical clustering Genome diagrams (GenomeDiagram) - Visualizing genomic features Quick example: from Bio.SeqUtils import gc_fraction, molecular_weight from Bio.Seq import Seq seq = Seq( "ATCGATCGATCG" ) print ( f"GC content: {gc_fraction(seq): .2 %} " ) print ( f"Molecular weight: {molecular_weight(seq, seq_type= 'DNA' ): .2 f} g/mol" ) General Workflow Guidelines Reading Documentation When a user asks about a specific Biopython task: Identify the relevant module based on the task description Read the appropriate reference file using the Read tool Extract relevant code patterns and adapt them to the user's specific needs Combine multiple modules when the task requires it Example search patterns for reference files: # Find information about specific functions rg -n "SeqIO.parse" references/sequence_io.md # Find examples of specific tasks rg -n "BLAST" references/blast.md # Find information about specific concepts rg -n "alignment" references/alignment.md Writing Biopython Code Follow these principles when writing Biopython code: Import modules explicitly from Bio import SeqIO, Entrez from Bio.Seq import Seq Set Entrez email when using NCBI databases; load only NCBI_API_KEY from the environment if present import os from Bio import Entrez Entrez.email = "your.email@example.com" Entrez.tool = "your_tool_name" if api_key := os.environ.get( "NCBI_API_KEY" ): Entrez.api_key = api_key Use appropriate file formats - Check which format best suits the task # Common formats: "fasta", "genbank", "fastq", "clustal", "phylip" Handle files properly - Close handles after use or use context managers with open ( "file.fasta" ) as handle: records = SeqIO.parse(handle, "fasta" ) Use iterators for large files - Avoid loading everything into memory for record in SeqIO.parse( "large_file.fasta" , "fasta" ): # Process one record at a time Handle errors gracefully - Network operations and file parsing can fail from urllib.error import HTTPError try : handle = Entrez.efetch(db= "nucleotide" , id =accession) except HTTPError as e: print ( f"Error: {e} " ) Common Patterns Pattern 1: Fetch Sequence from GenBank from Bio import Entrez, SeqIO Entrez.email = "your.email@example.com" # Fetch sequence handle = Entrez.efetch(db= "nucleotide" , id = "EU490707" , rettype= "gb" , retmode= "text" ) record = SeqIO.read(handle, "genbank" ) handle.close() print ( f"Description: {record.description} " ) print ( f"Sequence length: { len (record.seq)} " ) Pattern 2: Sequence Analysis Pipeline from Bio import SeqIO from Bio.SeqUtils import gc_fraction for record in SeqIO.parse( "sequences.fasta" , "fasta" ): # Calculate statistics gc = gc_fraction(record.seq) length = len (record.seq) # Find ORFs, translate, etc. protein = record.seq.translate() print ( f" {record. id } : {length} bp, GC= {gc: .2 %} " ) Pattern 3: BLAST and Fetch Top Hits from Bio.Blast import NCBIWWW, NCBIXML from Bio import Entrez, SeqIO Entrez.email = "your.email@example.com" # Run BLAST result_handle = NCBIWWW.qblast( "blastn" , "nt" , sequence) blast_record = NCBIXML.read(result_handle) # Get top hit accessions accessions = [aln.accession for aln in blast_record.alignments[: 5 ]] # Fetch sequences for acc in accessions: handle = Entrez.efetch(db= "nucleotide" , id =acc, rettype= "fasta" , retmode= "text" ) record = SeqIO.read(handle, "fasta" ) handle.close() print ( f"> {record.description} " ) Pattern 4: Build Phylogenetic Tree from Sequences from Bio import AlignIO, Phylo from Bio.Phylo.TreeConstruction import DistanceCalculator, DistanceTreeConstructor # Read alignment alignment = AlignIO.read( "alignment.fasta" , "fasta" ) # Calculate distances calculator = DistanceCalculator( "identity" ) dm = calculator.get_distance(alignment) # Build tree constructor = DistanceTreeConstructor() tree = constructor.nj(dm) # Visualize Phylo.draw_ascii(tree) Best Practices Always read relevant reference documentation before writing code Use grep to search reference files for specific functions or examples Validate file formats before parsing Handle missing data gracefully - Not all records have all fields Cache downloaded data - Don't repeatedly download the same sequences Respect NCBI rate limits - Use API keys, registered tool/email values for reusable software, and Entrez history/batching for large jobs Test with small datasets before processing large files Keep Biopython updated to get latest features and bug fixes Use appropriate genetic code tables for translation Document analysis parameters for reproducibility Troubleshooting Common Issues Issue: "No handlers could be found for logger 'Bio.Entrez'" Solution: This is just a warning. Set Entrez.email to suppress it. Issue: "HTTP Error 400" from NCBI Solution: Check that IDs/accessions are valid and properly formatted. Issue: "ValueError: EOF" when parsing files Solution: Verify file format matches the specified format string. Issue: Alignment fails with "sequences are not the same length" Solution: Ensure sequences are aligned before using AlignIO or MultipleSeqAlignment. Issue: BLAST searches are slow Solution: Use local BLAST for large-scale searches, or cache results. Issue: PDB parser warnings Solution: Use PDBParser(QUIET=True) to suppress warnings, or investigate structure quality. Issue: ImportError for Bio.HMM, Bio.MarkovModel, or Bio.Application Solution: These modules were removed in Biopython 1.86. Use hmmlearn for HMMs and the standard library subprocess module instead of Bio.Application CLI wrappers. Issue: PairwiseAligner returns fewer alignments after upgrading to 1.86+ Solution: The default gap score changed from 0 to -1 in 1.86, eliminating trivial tie alignments. Set aligner.gap_score = 0 to restore the old behavior if needed (see references/alignment.md ). Additional Resources Official Documentation : https://biopython.org/docs/latest/ Tutorial : https://biopython.org/docs/latest/Tutorial/ Cookbook : https://biopython.org/docs/latest/Tutorial/ (advanced examples)