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Machine learning in drug discovery

A practical introduction

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  • Course overview
  • Search within this course
  • What is machine learning?
  • ML in drug discovery: why now?
  • ML in the drug discovery pipeline
  • Getting started in ML using WEKA
    • Explorer
    • Experimenter
    • Knowledge Flow
    • Workbench
    • Simple CLI
  • Hands-on with WEKA
    • Loading data
    • Preprocessing data
    • Data visualisation
    • Principal Component Analysis in WEKA
    • Data clustering
    • Interpreting the results
  • Identifying targets for cancer using gene expression profiles
    • Dataset preprocessing
    • Model development
    • Model performance
    • Model interpretation
    • Interpreting the results
  • Other tools utilising ML or NLP for drug discovery
    • Open Targets Genetics
    • Europe PMC and Open Targets Platform
  • Summary
  • Your feedback
  • Learn more
  • References
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All materials are free cultural works licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, except where further licensing details are provided.

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Other resources and tutorials on WEKA

https://machinelearningmastery.com/use-machine-learning-algorithms-weka/

https://waikato.github.io/weka-wiki/

https://www.tutorialspoint.com/weka/index.htm

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