Graduate Program in Bioinformatics and Computational Biology (BCB)

The Graduate Program in Bioinformatics and Computational Biology (BCB) offers graduate study and research focused on the development and application of computational and mathematical models to biological problems, with an emphasis on high-throughput genomic and proteomic data. The Program in Bioinformatics and Integrative Biology has designed it's two Advanced Topic courses to complement the departments overriding goal: to educate talented and highly motivated women and men for research in the post-genomic era.

Specific topics of research and study include systems biology; analysis of regulatory and metabolic networks; structure of the genome and comparative genomics; population genetics and molecular evolution; protein-protein and protein-DNA interactions; RNA; modeling of large-scale biological systems; structural biology; protein folding and modeling; and biological physics. Students receive a rigorous training in modern bioinformatics and computational biology through integration of guided research, coursework and participation in seminar programs. The program aims to train a new generation of scientists with the multidisciplinary skill set for careers in cutting-edge, highly quantitative biomedical research.

The Program in Bioinformatics offers the following BCB courses:

An Empirical Introduction to Statistical Modeling | BBS 706

Advanced Topics in Bioinformatics | BBS 741