Faculty: Philip Bourne, Charles Elkan, James Fowler, Kelly Frazer, Terry Gaasterland, Nathaniel Heintzman, Trey Ideker, Yu-Tsueng Liu, Lucila Ohno-Machado, Pavel Pevzner, Sergei Pond, Shankar Subramaniam, Christopher Woelk, Eugene Yeo
This track links bioinformatics to health informatics through its special focus on methods and techniques that directly relate to the study of human health and disease. Computational methods related to genomics, transcriptomics, proteomics, and metabolomics are all included in this track, which connects molecular findings and phenotypes to characterize disease susceptibility or determine disease markers, and predict response to treatment and prognosis. Faculty from this track overlap with the ones in the Bioinformatics PhD Program who are directly involved with studying human disease using computational methods. Specialized areas are listed below:
- Structural and Functional Genomics emphasize statistical and machine learning methods for molecular profiling of diseases, correlation of common and rare genetic variants to phenotypes, and regulatory elements (e.g., discovery of new microRNAs from mRNA-seq, prediction of their targets, and use of information in machine learning classifiers to predict disease progression).
- Metagenomics cover computational techniques to discover and characterize infectious disease agents and determine their influence in pathogenesis and disease progression (e.g., phylogenetics for drug-resistant HIV variants).
- Biological networks, where techniques from systems biology and social network analysis are combined to study interactions among genes and their regulatory elements, proteins, metabolites, signal propagation, and integration of information across different biological levels.