•   When: Monday, April 29, 2019 from 11:00 AM to 12:00 PM
•   Speakers: Mona Singh, Princeton University
•   Location: Research Hall 163
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Abstract

Each cell in our body accomplishes its functions via a complex network of molecular interactions.    Analyses of these networks are thus key to understanding cellular functioning (and, in the case of disease, malfunctioning).  I will overview what has been discovered about the basic structure and organization of cellular networks, and present frameworks and algorithms that leverage these properties in order to gain a better understanding of diseases such as cancer.  

Bio

Mona Singh obtained her AB and SM degrees at Harvard University, and her PhD at MIT, all three in Computer Science. She did postdoctoral work at the Whitehead Institute for Biomedical Research. She has been on the faculty at Princeton since 1999, and currently she is Professor of Computer Science in the computer science department and the Lewis-Sigler Institute for Integrative Genomics. She works broadly in computational molecular biology, as well as its interface with machine learning and algorithms. Her group develops methods for interpreting genomes at the level of proteins, and is especially interested in developing data-driven methods for predicting and characterizing protein interactions, specificity, and networks---in both healthy and disease contexts. She is a Methods Editor at PLOS Computational Biology, has been program committee chair for several major computational biology conferences, including ISMB (2010), WABI (2010), ACM-BCB (2012), and RECOMB (2016), and has been Chair of the NIH Modeling and Analysis of Biological Systems Study Section (2012-2014). She received the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2001, and is an ISCB Fellow.