BMS5302 Machine learning: AI for bioinformatics

In this unit, you will explore the application of machine learning methods in bioinformatics, including both theoretical aspects and practical implementation. You will be introduced to the conceptual foundations and appropriate usage of algorithms for dimensionality reduction, clustering, classification and prediction as applied to the analysis of multi-omics and imaging data from biological studies.

You will become familiar with sound practices for all stages of machine learning analyses, including data pre-processing and feature selection through to model development, validation, and interpretation. You will learn to critically evaluate model performance, define the limitations of the algorithms used and interpret model predictions for both technical and non-technical audiences. A special emphasis will be placed throughout on how to select and implement machine learning approaches suitable to the biological context of a given research question.

This unit will develop your conceptual understanding and practical experience in applying machine learning techniques to complex biological data through online lectures, hands-on workshop sessions, and independent project work. By the end of the unit, you will be able to knowledgeably apply and evaluate the performance of machine learning algorithms to common analysis problems in bioinformatics.