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ComputingLifeSci

A complete computational biology curriculum — 23 courses covering programming, databases, machine learning, genomics and research infrastructure. Written for biologists, not computer scientists.

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Programming for Biology

Python for Biologists
R for Biologists
Perl for Biologists
MATLAB for Biologists
SAS for Biologists
BioJava for Biologists

Data & Databases

SQL for Biological Databases
Bioinformatics Databases
Big Data Mining for Biologists

AI & Machine Learning

Machine Learning for Biologists
Artificial Intelligence for Biologists
MLOps for Biologists
AI Tools for the Bioinformatics Lab

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Machine Learning for Biologists82 chapters

Overview
Case Study 12.1 — Cancer Classification from Gene Expression
Case Study 12.2 — Gene Expression Prediction (Regression)
Case Study 12.3 — Protein Function Prediction
Case Study 12.4 — Variant Classification (Pathogenic vs. Benign)
Case Study 12.5 — Microbiome-Based Disease Prediction
Case Study 12.6 — Drug Response Prediction
Case Study 12.7 — Plant Disease Detection from Leaf Images
Case Study 12.8 — Cell Image Classification (Microscopy)
Case Study 12.9 — Protein Subcellular Localization Prediction

/Machine Learning for Biologists/PART 12 — Case Studies

Chapter 60 of 821 min read

Case Study 12.8 — Cell Image Classification (Microscopy)

Dataset: Fluorescence or brightfield microscopy images of cells, labeled by cell type or state (e.g., cell cycle phase). Objectives: Automatically classify cells in high throughput microscopy screens, replacing slow…

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