Course Description
Development of computational methods to infer biological information from data, including DNA sequences, gene expression levels, epigenome, and microbiome data. Students will read research articles ranging from statistics to biology and conduct extensive data analysis. Focus on raw data processing as well as statistical learning methods for downstream analysis.
Athena Title
Adv Comp Bio and Bioinformatic
Prerequisite
STAT 8210
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
Students will learn advanced statistical methods used in the analysis of genomic, proteomic, and epigenomic data. Methods are organized around data types commonly found in biological experiments, such as DNA sequencing data, gene expression levels, histone modifications, and microbiome data. Emphasis on statistical understanding.
Topical Outline
The course is divided into three modules: Gene expressions, DNA sequence analysis, and regulatory network analysis. We will focus on raw data processing, bias correction, and other low level analysis for currently available bio-techniques, as well as statistical learning methods, such as classification and hidden Markov models, for downstream analysis. There are extensive data analysis assignments.