Nov 21, 2024  
Graduate School Course Catalog 2016-2017 
    
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Graduate School Course Catalog 2016-2017 [ARCHIVED CATALOG]

CISG 5202 - Introduction to Mathematical Methods in Computational Biology (3)

Prerequisites: First year graduate students or the consent of the instructor. A survey of the mathematics needed to understand Bioinformatics tools insightfully. Topics include algebra, statistics and graph theory. The material and examples will be presented in biological context to emphasize their relevance to biological findings. The course serves as a prerequisite for advanced courses in computational biology. The course will cover basic definitions and operations on matrices; combination, permutation, and first order logic; ordinary differential equations; basic probability theory; random variables; independence; conditional expectation; Bayes theorem; expectation and variance; commonly used distributions (discrete and continuous); multivariate distribution; statistical modeling; statistical inference; discrete Markov model; information and entropy; graphs and trees.


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