Bioinformatics & Computational Biology
The Department of Biostatistics offers a variety of educational and research opportunities in computational biology and bioinformatics. The master’s and doctoral programs in biostatistics both include newly developed bioinformatics curricula, each comprised of course sequences covering methodology and genomic data analysis, ranging from applications in molecular networks to the statistical theory of high-dimensional data analysis, and the new Master of Science in Computational Biology and Quantitative Genetics provides students with the rigorous quantitative training and essential skills needed to successfully meet the challenges presented by large-scale public health data — “Big Data” — in biomedical research.
The complementary Program in Quantitative Genomics (PQG) provides additional cross-departmental study opportunities, cross-disciplinary training, and a research and curriculum network spanning the School of Public Health.
Collaborative research with the biological programs within the school includes investigations of epigenetic modulators of health with respect to environmental exposures, host- and population-wide mutation analysis and host-pathogen interactions for a number of infectious agents, the metagenomic roles of the human microbiome in disease, functional analyses of single nucleotide polymoprhisms and structural variations, and the mechanisms tying stem cell differentiation and proliferation to cancer.
The Longwood Medical Area offers rich collaborative opportunities with Harvard Medical School and affiliated research hospitals. Cross-registration is available for courses offered by other Harvard institutions. The department trains doctoral students in bioinformatics to develop novel computational and statistical methods for biological data analysis and to collaborate closely with experimental biologists and physicians.