Examine typical data, data analysis, and algorithms encountered in computational biology. Includes introductory probability and statistics, basics of programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, synthetic biology, analysis of large-scale gene expression data, data clustering, biological pattern recognition, and biological networks. Three lecture hours a week for one semester. Biochemistry 339N and 364C may not both be counted. Prerequisite: Biochemistry 339F with a grade of at least B; Computer Science 303E or the equivalent; Statistics and Data Sciences 328M or 320E and 348 or 322E with a grade of at least B; and consent of the instructor.