CS/ST548: bioinformatics algorithms
Class was moved from engineering E206 to CSB 325
The past decade has seen an explosion of biological data, including the DNA sequence of a number of organisms. Computer science and statistics have an important role in analyzing these data: from assembling the genomic sequence, to predicting the protein-coding regions, their function and the manner in which they are regulated. The course will focus on biological sequence analysis, starting with the biological background, motivating the various computational problems, and methods for their solution. Computational techniques covered in the course include dynamic programming for sequence alignment, hidden Markov models for gene finding, and Gibbs sampling for motif discovery.
The course is aimed at graduate students interested in bioinformatics. It is expected that students from computer science, statistics, and the life sciences will benefit from such a course. It will provide a broad overview of the computational and statistical techniques currently used in bioinformatics. Students will obtain in-depth understanding of standard bioinformatics tools and learn to use various sources of sequence data. In homework assignments students will implement and use methods for analysis of protein/DNA sequences and other genomic information. The project component of the course will be centered around real biological data analysis problems, giving the student realistic experience in bioinformatics problem solving.