Lecture: 3 hours
Discussion: 1 hour
Prerequisite: Course 124, graduate standing in Computer Science of Life Sciences
Grading: Letter; project (60%), presentation (30%), class participation (10%)
Bioinformatics methods for analysis and inference of functional relationships among genes using large-scale genomic data, including methods for integration of gene expression, promoter sequence, TF-DNA binding and other data, and approaches in modeling of biological networks.
Expanded Course Description:
Selected technical papers and class notes will be used
Students will use methods taught in class to follow the process of gene regulation inference from available data. Both theoretical and applied projects will be suggested. The projects will be done in groups consisting of a fair mix of life science and computer science students.
Students will present technical papers or software used for gene regulation inference.
Possible use for projects.
Instructor: V. Filkov
Prepared by: V. Filkov (February 2006)
There is no significant overlap with other courses.