May 18, 2024  
Graduate Catalog | 2016-2017 
    
Graduate Catalog | 2016-2017 Previous Edition

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BINF 6210 - Machine Learning for Bioinformatics


Credit Hours: (3)

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.

Prerequisite(s): BINF 6200 , BINF 6200L , and Calculus.
Most Recently Offered (Day): Fall 2016, Fall 2015, Fall 2014
Most Recently Offered (Evening): Course has not been offered at this time in the past 3 years


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