Bioinformatics and Computational Biology Program

The Program in Bioinformatics and Computational Biology (BCB) offers graduate study and research focused on the development and application of computational and statistical methods to answer biological and medical questions, with an emphasis on the high-throughput genomic, epigenomic, and transcriptomic data, increasing available from single cells. Specific topics of research and study include:

• Functional genomics, epigenomics, and transcriptomics
• Comparative genomics, epigenomics, and transcriptomics in the human population and across species
• Analysis of regulatory and metabolic networks
• Higher-order genomic structure and regulation
• Population genetics and molecular evolution
• Gene regulation protein-DNA interactions
• Mendelian traits, complex traits, and phylogenetics
• Modeling of large-scale biological systems
• Visualization of complex genetic datasets
• Application of machine learning to biomedical questions

Through the integration of guided research, coursework, and participation in seminar programs, students receive rigorous training in state-of-the-art computational, statistical, and machine learning methods for addressing biological questions. The program bridges the gap between experimental biologists and computational scientists and prepares students for careers in cutting-edge, quantitative biomedical research.

REQUIREMENTS FOR SPECIALIZATION

All Basic Biomedical Science students must complete the core curriculum as well as electives required by their program. Students in the Bioinformatics and Computational Biology program must take 3 graded elective courses of 2-4 credits each, two of which must be in Bioinformatics. Students choose elective courses from among those offered by the program, or relevant courses offered by other GSBS programs. The plan of coursework is designed to be flexible in order to accommodate each student’s needs and areas of interest.

View PhD Program Schedule  |  View Courses

OUR LEADERSHIP & FACULY

OUR STUDENTS

PUBLICATIONS

A number of students in the BCB program have been involved in the research and subsequent publications of the ENCODE Consortium. ENCODE is a public research consortium aimed at identifying all functional elements in the human and mouse genomes. Articles about this research have appeared in leading journals such as:

• An Integrated Encyclopedia of DNA Elements in the Human Genome. Nature. 2012 Sep 6; 489(7414):57-74. doi: 10.1038/nature11247.  BCB students including Jiali Zhuang in the Weng Lab, Bryan Lajoie in the Dekker Lab and faculty members Zhiping Weng and Job Dekker co-authored this article.
• Expanded Encyclopedias of DNA Elements in the Human and Mouse Genomes. Nature. 2020 July 29. BCB students Jill Moore, Michael Purcaro, and Henry Pratt from the Weng lab were co-first authors as they made major contributions to data analysis, and Prof. Zhiping Weng was a co-corresponding author, leading the data analysis effort for this paper.

BCB students have also been involved in the research of the PsychENCODE Consortium. The PsychENCODE Consortium aims to produce a public resource of multidimensional genomic data using tissue- and cell type-specific samples from phenotypically well-characterized, high-quality, healthy and disease-affected human post-mortem brains, and to functionally characterize disease-associated regulatory elements and variants in model systems. Articles describing PsychENCODE research include:

• Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk.
  Science. 2018 Dec 14; 362(6420):eaat4311. doi: 10.1126/science.aat4311.  PMID: 30545851 PMCID: PMC6408958. BCB student Tyler Borrman was a co-first author and his mentor Prof. Zhiping Weng was a co-corresponding author of this article.
• Comprehensive Functional Genomic Resource and Integrative Model for the Human Brain. Science. 2018 Dec 14; 362(6420):eaat8464. doi: 10.1126/science.aat8464. BCB student Jill Moore and her mentor Prof. Zhiping Weng co-authored this article.

BCB students co-authored a number of papers in leading journals:

• Yuming Cao, Garber Lab
  Cell. 2020 May 28;181(5):1016-1035.e19. doi: 10.1016/j.cell.2020.04.035. Epub 2020 Apr 27. SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets Across Tissues.
• Kyle Gellatly, Garber Lab
  Nature Immunology. 2020 Mar;21(3):274-286. doi: 10.1038/s41590-020-0593-9. Epub 2020 Feb 17. HIV-1-induced Cytokines Deplete Homeostatic Innate Lymphoid Cells and Expand TCF7-dependent Memory NK Cells.
• Jill Moore, Weng Lab
  Genome Biology. 2020 Jan 22;21(1):17. doi: 10.1186/s13059-019-1924-8. A Curated Benchmark of Enhancer-Gene Interactions for Evaluating Enhancer-Target Gene Prediction Methods.
• Tyler Borrman, Weng Lab
  Proteins. 2019 Dec;87(12):1200-1221. doi: 10.1002/prot.25838. Epub 2019 Oct 25. Blind Prediction of Homo- And Hetero-Protein Complexes: The CASP13-CAPRI Experiment.
• Serkin Sayin, Mitchell Lab
  PLoS Biology. 2019 Jun 26;17(6):e3000348. doi: 10.1371/journal.pbio.3000348. eCollection 2019 Jun. Harnessing Robotic Automation and Web-Based Technologies to Modernize Scientific Outreach
•  Xue Li, Karlsson Lab
  Genes. 2019 Jun 7;10(6):433. doi: 10.3390/genes10060433. BarkBase: Epigenomic Annotation of Canine Genomes.
• Jiali Zhuang, Weng Lab
  Nucleic Acids Research. 2015 Sep 30;43(17):8146-56. doi: 10.1093/nar/gkv831. Epub 2015 Aug 17. Local Sequence Assembly Reveals a High-Resolution Profile of Somatic Structural Variations in 97 Cancer Genomes.

POST-DEGREE CAREERS

The BCB program has prepared students for careers at leading companies and academic institutions in the field of Bioinformatics.