
A Department of Computational Biology Seminar
Featuring Dr. Mona Singh, Wang Family Professor in Computer Science, Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University
Networks of molecular interactions underlie virtually all functions executed within a cell. Networks thus provide a powerful foundation within which to interpret a wide range of rapidly accumulating biological data.
In this talk, I will present formulations and algorithms that leverage the structure and function of biological networks in order to discern the effects of disease mutations.
First, I will introduce a framework that can rapidly integrate multiple sources of information about molecular functionality in order to discover key interactions within a network that tend to be disrupted in cancers. Crucially, our approach is based on analytical calculations that obviate the need to perform time-prohibitive permutation-based significance tests.
Second, I will discuss methods for uncovering noncoding mutations that can alter regulatory networks in cancer. Finally, I will describe an approach that leverages large compendia of DNA-binding specificities for transcription factors in order to infer protein-DNA interaction interfaces and uncover the effects of mutations within transcription factors. Overall, our work showcases the versatility and power of a network viewpoint in advancing biomedical discovery.
Date & Time
January 20, 2023
3:00 pm - 5:00 pm
Location
More information about this event.
Contact Information
Speaker
Dr. Mona Singh, Wang Family Professor in Computer Science Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics Princeton University
Departments
Computational Biology
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