bioinformatics

name	bioinformatics
description	Computational biological data analysis
license	MIT
compatibility	opencode
metadata	{"audience":"bioinformaticians, computational biologists, researchers","category":"biology"}

What I do

• Analyze and interpret large-scale biological datasets
• Perform sequence alignment and homology modeling
• Develop algorithms for biological data processing
• Create and maintain biological databases
• Predict protein structure and function
• Identify biomarkers and genetic variants

When to use me

• When analyzing genomic, proteomic, or transcriptomic data
• When searching sequence databases (BLAST, FASTA)
• When predicting protein structure or function
• When identifying variants from sequencing data
• When building phylogenetic trees
• When analyzing gene expression patterns

Key Concepts

Sequence Analysis

Alignment Algorithms

• Needleman-Wunsch: Global alignment
• Smith-Waterman: Local alignment
• BLAST: Heuristic local alignment
• FASTA: Fast sequence similarity search

# Example: Simple sequence alignment scoring
def simple_align(seq1, seq2, match=1, mismatch=-1, gap=-2):
    """Calculate simple alignment score."""
    score = 0
    for a, b in zip(seq1, seq2):
        if a == b:
            score += match
        else:
            score += mismatch
    return score

Biological Databases

• NCBI (GenBank, PubMed, BLAST)
• UniProt: Protein sequences and function
• PDB: Protein structures
• Ensembl: Genome annotations
• UCSC Genome Browser

Data Formats

• FASTA: Sequence data
• FASTQ: Sequences + quality scores
• SAM/BAM: Sequence alignment
• VCF: Variant calls
• PDB: Protein structure
• GO: Gene Ontology annotations