Mathematics

# MATH 7340: Statistics for Bioinformatics

Lecture - 4 credits

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- Introduces the concepts of probability and statistics used in bioinformatics applications, particularly the analysis of microarray data.
- Uses statistical computation using the open-source R program.
- Topics include maximum likelihood; Monte Carlo simulations; false discovery rate adjustment; nonparametric methods, including bootstrap and permutation tests; correlation, regression, ANOVA, and generalized linear models; preprocessing of microarray data and gene filtering; visualization of multivariate data; and machine-learning techniques, such as clustering, principal components analysis, support vector machine, neural networks, and regression tree.

Introduces the concepts of probability and statistics used in bioinformatics applications, particularly the analysis of microarray data.

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