Prerequisites: CS 111; CS 141 or CS 218; STAT 155 or STAT 160A; graduate standing
Description: A study of computational and statistical methods aimed at automatically analyzing, clustering, and classifying biomolecular data. Includes combinatorial algorithms for pattern discovery; hidden Markov models for sequence analysis; analysis of expression data; and prediction of the three-dimensional structure of RNA and proteins.
Credit: May be taken Satisfactory (S) or No Credit (NC) with consent of instructor and graduate advisor. Credit is awarded for one of the following CS 234 or CS 144.
Referenced in
- Biomedical Sciences Graduate Program — Master’s Degree
- Computer Science and Engineering — Graduate Program
- Data Science, Computational — Master’s Degree
- Genetics, Genomics, and Bioinformatics — Doctoral Degree
- Mechanisms of Gene Expression and Regulation Studies Designated Emphasis — Designated Emphasis Requirements