Statistics for Bioinformatics
Introduction to the theory and applications of statistical methodology in the biological sciences. Topics include inference, stochastic processes, Markov chains, hidden Markov models, clustering, and gene expression analysis. Applications to current molecular biology and genetics problems. No biology background required. Prerequisite: MATH 161A (with a grade of "C-" or better) or instructor consent.
Normal Grade Rules