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The research conducted in Troyanskaya Laboratory focuses on understanding the immensely complex molecular network of interactions that form the foundation of human biology and disease. Employing genomic approaches, the team aims to provide an illuminating window into biological systems through advanced analyses. The primary goal is to interpret and distill this complexity into accurate modeling of molecular pathways, particularly those malfunctioning in relation to disease manifestation. The laboratory is dedicated to inventing integrative methods for systems-level pathway modeling and genome-scale dataset analysis. They apply these approaches to tackle challenging biological problems, specifically examining how pathways function across diverse cell types that dynamically shift in response to genetic and pharmacological perturbations. Achieving these scientific goals requires the development of innovative computational methods to analyze and model the diverse high-throughput “big data” encountered in biology. The interdisciplinary team — comprising experts in bioinformatics, machine learning, statistics, algorithms, and biology — works collaboratively with experimental and clinical researchers to translate computational predictions into testable hypotheses. Their focus spans various diseases, including autism, Alzheimer's disease, kidney disease, and breast cancer, aiming to produce dynamic predictive models that elucidate the molecular bases of these conditions.
GRE scores are not accepted. Ph.D. is the primary degree; students are not required to hold an M.S.E. prior to admission.