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Bio for Devs_

Biology for people who think in code

A complete guide to molecular and cell biology for software developers entering bioinformatics and computational biology — with real code examples and computational analogies throughout.

9Parts
49+Chapters
8Code Labs
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// What is this?

Computational Analogies

Every biological concept is paired with a software equivalent. DNA is source code. Proteins are executables. The cell membrane is a firewall.

Real Code Examples

Each part ends with a practical chapter using Biopython, NetworkX, MNE-Python, and other bioinformatics tools.

Progressive Depth

From cell basics to computational neuroscience and ML in biology — structured like a well-architected codebase.

// The Curriculum
// Who is this for?
💻

Software Developers

Transitioning into biotech, genomics, or healthtech and need the biology foundation.

📊

Data Scientists

Working with biological datasets and need to understand what the numbers actually mean.

🤖

ML Engineers

Building models on genomics, protein structures, or brain signals and need domain context.

🔬

Researchers

Coming from biology and want to deeply understand the computational side of their field.