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Mona Singh, Ph.D.: Predicting and Analyzing Cellular Networks


High-throughput experimental technologies, along with computational predictions, have resulted in large-scale biological networks for numerous organisms. Global analyses of biological networks provide new opportunities for revealing protein functions and pathways and for uncovering cellular organization principles. Prof. Singh will discuss a number of approaches her group has developed over the years for the complementary problems of predicting interactions and analyzing interaction networks. First, she will describe a general framework for predicting protein interactions mediated by specific structural domains and show how this framework can be used to predict a large class of regulatory interactions. Next, she will describe algorithms for analyzing protein interaction networks to uncover protein function and functional modules. Finally, she will present a framework for explicitly incorporating known attributes of individual proteins into the analysis of biological networks and use it to discover recurring network patterns underlying a range of biological processes.


Mona Singh is an Associate Professor with tenure in the Department of Computer Science and the Lewis-Sigler Institute for Integrative Genomics at Princeton University. She conducted her postdoctoral research at the Whitehead Institute for Biomedical Research. Prof. Singh received the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2001 and the Rheinstein Faculty Award in 2003. She received her AB and SM in Computer Science from Harvard University and her PhD in Computer Science from the Massachusetts Institute of Technology.