Winter 2022 STAT 35450

Course: STAT 35450=HGEN 48600

Title: Fundamentals of Computational Biology: Models and Inference

Instructor(s): Matthew Stephens

Class Schedule: Sec 1: TR 3:30 PM–4:50 PM in BSLC 008

Office Hours: 

Textbook(s): Ross, Introduction to Probability Models (12th ed)

Description: Covers key principles in probability and statistics that are used to model and understand biological data. There will be a strong emphasis on stochastic processes and inference in complex hierarchical statistical models. Topics will vary but the typical content would include: Likelihood-based and Bayesian inference, Poisson processes, Markov models, Hidden Markov models, Gaussian Processes, Brownian motion, Birth-death processes, the Coalescent, Graphical models, Markov processes on trees and graphs, and Markov Chain Monte Carlo.

Prerequisite(s): STAT 24400