Course: STAT 35450=HGEN 48600
Title: Fundamentals of Computational Biology: Models and Inference
Instructor(s): John Novembre and Matthew Stephens
Teaching Assistant(s):
Class Schedule: Sec 1: TR 3:30 PM–4:50 PM in BSLC 218
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, Markov Chain Monte Carlo.