Overview
Introduction to Biology: A Generative Approach is an open biology textbook with forty-four chapters, ranging from systems science and chemical foundations through cells, metabolism, genetics, microbiology, physiology, evolution, and ecology. Organized as Unit 0 plus Units I–X, the text presents biology as an evidence-grounded discipline in which mechanisms, measurements, and simple models are developed together, so readers can move between narrative explanation and the quantitative constraints that shape biological claims. Five recurring themes—evolution, information, structure and function, systems and emergence, and the cell—provide orientation across scales and align with mainstream undergraduate biology competencies; Unit 0 adds an optional systems, historical, and philosophical lens without replacing the traditional molecular-to-ecological sequence.
Where the curriculum is quantitative, corresponding computations live in tested code modules organized by domain (biochemistry, cell biology, genetics, physiology, ecology, evolution, microbiology, botany, and neuroscience), and many figures and process diagrams are generated programmatically rather than supplied as static artwork alone. The edition pairs each chapter with a paper-based laboratory activity and a question bank that progresses from recall to synthesis; model answers are visible in this instructor build. Primary literature is cited inline, glossary and curriculum-mapping appendices support course design, and the manuscript is maintained as a reproducible open-science artifact (source at https://github.com/docxology/biology_textbook ; archived at DOI 10.5281/zenodo.20286478). Text is released under Creative Commons Attribution 4.0; accompanying source code under Apache-2.0.
Overview source: Curated paper metadata.
Methods and contributions
Read the source for the full argument, qualifications, and evidence.
Findings and contributions
- The book covers introductory biology in a systems unit plus Units I-X with 44 core chapters, plus optional laboratories and question banks.
- Each chapter is followed by a companion lab and a 30-item question bank in the same canonical order.
- The author positions active inference and the free energy principle as optional graduate-depth lenses, not part of the introductory canon.
- The text includes a master glossary of 225 terms with etymology and chapter cross-references, and is released under CC BY 4.0.
- The stated pedagogical philosophy is to understand biology by computing biology.
Methods
- Generation from version-controlled Markdown, tested Python, and Mermaid diagrams — The open textbook is built from Markdown manuscript sources, tested Python modules, programmatically generated figures and rendered Mermaid diagrams.
- Python modules for models such as Michaelis-Menten and Hodgkin-Huxley — Each quantitative model introduced in a chapter exists as a working module in the codebase, used to generate figures.
- Manifest-driven organisation from manuscript/config.yaml — Navigation, scope tables and appendix ordering are generated from a single config.yaml manifest so they stay aligned with the rendered table of contents.
- Five Big Ideas mapped to AAAS Vision and Change core concepts — The book organises recurring themes as Five Big Ideas aligned pedagogically to the Vision and Change report's five core concepts.
Summary sources: Paper metadata and evidence · Extracted source text.
PDF downloads
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- biology_textbook_v1_05-26-2026-compressed.pdf PDF · 10.94 MiB · extracted-text source
Citation
Citation metadata follows the unified bibliography.
Catalog details and resources
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