Resources for Learning Bioinformatics and Computational Biology

Website in progress, planning to add more and clean up formatting.

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Programming Basics

• Important
  • Python (Caleb Curry)
  • alternative: Python (freeCodeCamp)
  • Python Data Analysis - NumPy, Pandas, Matplotlib (freeCodeCamp)
  • R (freeCodeCamp)
  • Linux / Unix (Caleb Curry)
  • Bash (Caleb Curry)
  • SQL (Caleb Curry)
  • alternative: SQL (freeCodeCamp)
  • Database Design (Caleb Curry)
  • alternative: Database Design (freeCodeCamp)
  • Algorithms and Data Structures (freeCodeCamp)
• Extra
  • C++ (Caleb Curry)
  • alternative: C++ (freeCodeCamp)
  • Java (Caleb Curry)
  • alternative: Java (freeCodeCamp)
  • Javascript (Caleb Curry)
  • alternative: Javascript (freeCodeCamp)
  • C (Caleb Curry)
  • alternative: C (freeCodeCamp)
  • HTML (freeCodeCamp)
  • CSS (freeCodeCamp)
  • University Course: Intro to Computer Science (Harvard)

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Machine Learning

• Important
  • Statistics (StatQuest)
  • alternative: Statistics (freeCodeCamp)
  • Machine Learning Basics (StatQuest)
  • alternative: Machine Learning Basics (freeCodeCamp)
  • Neural Networks From Scratch (Andrej Karpathy)
  • Machine Learning with Python (Sentdex)
  • PyTorch (Sentdex)
  • alternative: PyTorch (freeCodeCamp)
  • Neural Networks From Scratch (Sentdex)
  • University Course: Machine Learning with Andrew Ng (Stanford)
• Extra
  • PyTorch Practice - Melanoma Image Classifier (My Youtube Channel)
  • Reinforcement Learning (Sentdex)
  • Scikit-Learn Python Library (Sentdex)
  • Statistics and Machine Learning in R (StatQuest)

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Biology Review

• Important
  • High School Biology (Khan Academy)
  • AP / College Biology (Khan Academy)
• Extra
  • Biochemistry (Professor Dave Explains)
  • Anatomy and Physiology (Professor Dave Explains)
  • Crash Course Biology (CrashCourse)

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Bioinformatics and Computational Biology

• Important
  • Transcriptomics / RNA-seq: Overview and Data Analysis (StatQuest)
  • Bioinformatics 101 (Bioinformagician)
  • University Course: Computational Biology (MIT)
  • Single-Cell RNA-seq (Bioinformagician)
• Extra
  • Assorted Computational Biology Videos (My Youtube Channel)
  • BLAST for Protein Sequence Analysis (My Youtube Channel)
  • File Formats (Bioinformagician)
  • Various Bioinformatics Examples (Bioinformagician)
  • Drug Discovery with Python and Machine Learning (freeCodeCamp)
  • RNA-seq: Raw Data Processing (Chipster Tutorials)
  • University Course: Foundations of Computational and Systems Biology (MIT)
  • University Course: Statistical Methods in Computational Biology (UCLA)
  • Bioinformatics in Python (rebelScience)
  • sandbox.bio
  • Single Cell Best Practices
  • Saniya Khullar's Youtube Channel
  • Computational Biology Resources List (Claus Volko)
  • Computational Biology Resources List (Svetlana Ugarcina Perovic)

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Mathematical Biology

• Important
  • Numerical Methods and ODE Solvers (Jacob Bishop)
  • Modeling and Simulation of Gene Regulatory Networks (My Youtube Channel)
  • University Course: Mathematical Biology (UC Irvine)
  • University Course: Systems Biology (MIT)
  • Assorted Math Models in Biology (My Youtube Channel)
• Extra / Prerequisites
  • Algebra (freeCodeCamp)
  • alternative: Algebra with Python (freeCodeCamp)
  • Precalculus (freeCodeCamp)
  • Calculus 1 (freeCodeCamp)
  • Calculus 2 (freeCodeCamp)
  • Linear Algebra (freeCodeCamp)

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Textbooks

• Important
  • An Introduction to Systems Biology: Design Principles of Biological Circuits (Uri Alon)
  • Neural Networks From Scratch (Sentdex)
  • Deep Learning (Goodfellow, Bengio, Courville)
  • A First Course in Systems Biology (Eberhard Voit)
  • Dynamic Systems Biology Modeling and Simulation (DiStefano)
• Extra
  • Nonlinear Dynamics and Chaos (Strogatz)

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Regular Books

• Important
  • The Selfish Gene (Richard Dawkins)
  • The Emperor of All Maladies (Siddhartha Mukherjee)
  • The Signal and the Noise (Nate Silver)
  • The Gene (Siddhartha Mukherjee)
  • The Song of the Cell (Siddhartha Mukherjee)
• Extra
  • How to Survive a Plague (David France)
  • Chaos (James Gleick)
  • The Information (James Gleick)
  • p53: The Gene that Cracked the Cancer Code (Sue Armstrong)
  • Malignant (Vinay Prasad)