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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.


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



Zhiping Weng, PhD
Professor and Director, Program in Bioinformatics and Integrative Biology
Li Weibo Chair in Biomedical Research
email Dr. Weng


View the affiliated faculty listing for the Bioinformatics & Computational Biology Program or learn more about a few of our prominent labs: Weng Lab, Colubri Lab, Garber Lab, Karlsson Lab, and Lim Lab



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.


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


Weng Lab, November 2020

PACT Pharma, San Francisco, CA

Dissertation: Measuring Stability of 3D Chromatin Conformations and Identifying Neuron Specific Chromatin Loops Associated with Schizophrenia Risk


Bailey Lab, July 2017

Harvard University, Cambridge, MA

Dissertation: Genomic and Transcriptomic Investigation of Endemic Burkitt Lymphoma and Epstein Barr Virus.


Dekker Lab, February 2016

Illumina, San Diego, CA

Dissertation: Computational Approaches for the Analysis of Chromosome Conformation Capture Data and Their Application to Study Long-Range Gene Regulation.


Weng Lab, October 2017

UMASS Medical School, Worcester, MA

Dissertation: Defining a Registry of Candidate Regulatory Elements to Interpret Disease-Associated Genetic Variation.


Bailey Lab, April 2019

Harvard T.H. Chan School of Public Health in Biostatistics
Cambridge, MA

Dissertation: Comprehensive Computational Assessment And Evaluation of Epstein Barr virus (EBV) Variations, miRNAs, And EBERs in eBL, AML And Across Cancers.


Weng Lab, October 2015

Voyager Therapeutics, Cambridge, MA

Dissertation: Unveiling Molecular Mechanisms of piRNA Pathway from Small Signals in Big Data.


Weng Lab, September 2015

Molecular Stethoscope, San Diego, CA

Dissertation: Structural Variation Discovery and Genotyping from Whole Genome Sequencing: Methodology and Applications.