Introduction to Computational Molecular Biology

Dr. X. Liu
5 credits
Lectures, laboratories. Two 1.5-hour sessions each week.

Graduate entry level course to basic problems, algorithms and data analysis methods in computational biology. Topics covered in the course include sequence alignment, gene finding and annotation, microarray analysis, gene regulatory network, RNA/protein structure prediction, proteomics and pharmacogenetics. The course is targeted towards graduate students and postdocs in Biostatistics Department and Division of Biological Sciences.
Course Note: Lab or section will be announced at first meeting; cross-listed course, HSPH students must register for HSPH course.
Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.