Provides a basic understanding of the major challenges presented by the wealth of data flowing out the Human Genome Project and other sequencing efforts. Provides a theoretical framework for approaching these problems, rooted in machine learning and artificial intelligence. Provides information on tools and techniques to solve real biological problems. Developed algorithms for protein homology detection, multiple alignment, phylogenetic inference, gene finding, and DNA microarray analysis. Most courses 4000-level and above can be credited to all degree programs.
All courses are subject to advisor approval.
Working knowledge of at least one programming language. Access to the web. Some background in probability and statistics, at least as much as might be obtained by taking an upper division undergraduate course. Students do not need advanced knowledge in both computer science and biochemistry, although we expect all students to be familiar with one of these fields and ready to learn about the other. Within the next year the human race will see its own genome for the first time.