Computational Biology and Data Science

BMS Faculty in Computational Biology and Data Science

Research Area Leaders: Bing Ren & Gene Yeo

The Computational Biology and Data Science Research Area is a unique joint effort between several departments at UC San Diego: the Departments of Cellular & Molecular Medicine, Pediatrics, Medicine, Psychiatry and Pathology in the School of Medicine, and Computational Science and Engineering and Bioengineering on the UC San Diego main campus.

The overall goal of this research area is to provide students with a deep understanding of the development and application of computational, integrative modeling and engineering approaches to solving basic and translational problems in biology and medicine.

Computational Biology and Data Science faculty associated with this area research a broad range of topics, from large-scale studies of genetics, genomics, microbiome and epigenomics using cutting-edge biochemical and molecular technologies, coupled with advanced computational methods such as machine learning and network analyses. Faculty focus on these areas of biological inquiry: gene regulation, stem cell biology, cancer, malaria and genetic diseases. Engineering and material sciences approaches also tackle emerging opportunities in single cell genomics and biology.

The research area is tightly integrated with several training programs on campus, including Genetics, Bioinformatics and Systems Biology, Cancer Biology, and Quantitative Biology. Grants support funded students with specialized training opportunity and an intellectually coherent framework with opportunities for interacting with colleagues in the chosen research area.

BMS provides a unified core curriculum for all first-year students. Based on their interests, students can choose from a range of elective courses to fill their 15-unit elective requirement. Courses related to this research area are listed below

Elective Courses 

Genetics Journal Club (1 unit)

Students meet weekly to read and critically analyze recent papers in the field.