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Oct 31, 2024
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BINF 6210 - Machine Learning for Bioinformatics
Introduction of commonly used machine learning methods in the field of bioinformatics. Topics include: dimension reduction using principal component analysis, singular value decomposition, and linear discriminant analysis, clustering using kmeans, hierarchical, expectation maximization approaches, classification using k-nearest neighbor and support vector machines. To help understand these methods, basic concepts from linear algebra, optimization, and information theory are explained. Application of these machine learning methods to solving bioinformatics problems are illustrated using examples from the literature.
Credit Hours: (3)
Prerequisite(s): BINF 6200 and Calculus.
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