Python & Biopython for Biologists

From Python Basics to Structural Bioinformatics & Molecular Docking. A 21-day program for biologists with no prior coding experience — covering Python fundamentals, Biopython, BLAST automation, multiple sequence alignment, PDB structural analysis, network analysis, and molecular docking with AutoDock Vina.

Program Overview

This 21-day module is designed for biologists and life-science students who want to harness Python and Biopython for real-world bioinformatics. No prior programming experience is required. Each day builds on the last, starting from Python fundamentals and progressing through sequence analysis, structural bioinformatics, network analysis, and molecular docking.

Python Foundations for Biologists

• Python Setup & Biology Mindset — Google Colab, variables, data types (str, int, float, bool), print(), input(). Project: store and print a DNA sequence.
• Strings & Sequence Manipulation — indexing, slicing, upper(), replace(), count(), f-strings, manual GC% calculation.
• Lists, Tuples & Biological Collections — append, sort, nested lists for residue matrices, multi-sequence storage.
• Dictionaries & Biological Mappings — codon tables, amino-acid property maps, hydrophobicity scales as dict.
• Loops & Conditional Logic — for/while, if/elif/else, list comprehensions for filtering sequences.
• Functions & Reusable Bio-Code — def, default args, docstrings, custom gc_content(), reverse_complement(), translate_seq().
• File I/O, NumPy & Matplotlib — FASTA parsing with open(), NumPy arrays, bar/line/histogram plots. Project: GC% across sliding windows.

Biopython Core

• Biopython Intro & Bio.Seq — Seq object: complement, reverse_complement, transcribe, translate; SeqRecord attributes.
• FASTA & GenBank with SeqIO — SeqIO.read/parse/write, multi-FASTA iteration, GenBank CDS feature extraction.
• Entrez & NCBI Access — Entrez.efetch for nucleotide/protein, Bio.Medline for PubMed, rate-limit etiquette. Project: fetch BRCA1 mRNA.
• BLAST & Homology Searching — NCBIWWW.qblast (blastp/blastn), parse XML with NCBIXML, plot top hits.
• Multiple Sequence Alignment & Phylogenetics — ClustalW/MUSCLE wrappers, Bio.Phylo Newick trees, ASCII tree drawing.
• Restriction Enzymes, Motifs & SeqUtils — Bio.Restriction (EcoRI, BamHI), Bio.motifs, molecular weight, isoelectric point.
• PDB Parsing & Structural Bioinformatics — Bio.PDB, PDBParser, PDBList, structure hierarchy, B-factor and hydrophobicity plots.

Advanced Biopython & Applied Projects

• Structural Superimposition — Bio.SVDSuperimposer: set(), run(), get_rms(), RMSD interpretation, rotation/translation matrices.
• Network Analysis of BLAST Results — NetworkX DiGraph, edge weights from bit scores, interactive Plotly visualisations.
• Molecular Docking with Python — receptor/ligand prep, AutoDock Vina via Python subprocess, parsing binding affinities.
• Pandas for Biological Data — DataFrame creation, filtering, grouping, merging annotation with expression data, CSV export.
• Dimensionality Reduction & Clustering — PCA, KMeans, DBSCAN on protein feature matrices (length, GC%, MW, pI).
• Pipeline Automation — end-to-end: fetch → BLAST → parse → visualise; os, subprocess, pathlib, logging.
• Capstone Project — full structural + sequence analysis of a target protein with publication-ready figures.

Tools You Will Master

Python 3, Biopython, NumPy, Pandas, Matplotlib, Plotly, NetworkX, scikit-learn, RDKit (intro), AutoDock Vina, Google Colab.