An introduction to probabilistic modeling with emphasis on its use in biology. Fundamental concepts such as conditional probability and conditional expectation are studied in depth in order to prepare for an introduction to the theory and applications of Markov chains. Applications in biology may include birth-and-death processes, branching processes, sequence alignment, population genetics, epidemic processes, molecular evolution, and phylogenetic tree construction. (This course or MATH 3328 will be offered every other year.) Prerequisite: MATH 1320 or MATH 3320 or MATH 3334.
3 credits
Upper Division