For years, teaching bioinformatics meant building the same lecture over and over: here is the biological concept, here is the Python script that operationalizes it, here is what a student needs to understand before either one makes sense. Over time those notes accumulated into something larger than any single course, a full walk through computational biology built around a simple pairing: show the classic method first, then show what changes when AI enters the workflow.
That collection is now a book. Bioinformatics with AI: A Modern Introduction covers fourteen chapters, moving from the language of life and the central dogma through Python fundamentals and biological data, into sequence alignment, gene expression, and protein structure, and finally into the AI-native territory of genome analysis, metagenomics, single-cell data, and large language model reasoning applied to real bioinformatics problems. It closes with pipeline-building and capstone work, the kind of projects meant to be lived in rather than read once.
None of this started as a product. It started as class notes, refined semester over semester because the alternative, watching students struggle with the same conceptual gaps year after year, was not acceptable. Cleaning those notes into a finished book and releasing them without a paywall or login felt like the natural conclusion of that process rather than a departure from it.
The book is published through Envoi Publishing, ISBN 978-1-890222-12-3, and is hosted permanently at the link below for anyone teaching, learning, or simply curious about where biology and AI now intersect.
🔗 carywoods.github.io/biobook2