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Troyanskaya Laboratory focuses on the immensely complex molecular network of interactions that forms the foundation of human biology and disease. Utilizing genomic approaches, the research interprets and distills this complexity through accurate analysis and modeling of molecular pathways, particularly those that malfunction and lead to disease manifestation. The lab is dedicated to inventing integrative methods for systems-level pathway modeling and analytic techniques for genome-scale datasets. This research involves studying challenging biological problems and understanding pathway functions across diverse cell types, with dynamic changes in response to genetic or pharmacological perturbations. The team's interdisciplinary approach combines bioinformatics, machine learning, statistics, algorithms, and biology, allowing for the translation of computational predictions into testable hypotheses in collaboration with experimental clinical researchers. Key research interests include autism, Alzheimer's disease, kidney disease, and breast cancer, aiming for high-resolution predictive models that elucidate molecular bases of diseases through genetic and environmental perturbations.
GRE scores are not accepted. Ph.D. is the primary degree; students are not required to hold an M.S.E. prior to admission.