At #UCDavis Leonid Chindelevitch, 10/09/14 “Probing Networks to Understand Nature”

Department of Computer Science Colloquium Seminar Series

Speaker: Leonid Chindelevitch

Harvard, MIT

Host: Dan Gusfield

WHEN: Thurs. Oct 9, 2014 3:10pm

WHERE: 1131 Kemper Hall

Title: Probing Networks to Understand Nature

Abstract: Networks are a fundamental tool for understanding the intricate interconnections that govern biological systems. This talk will describe two ways in which networks, in combination with mathematical models and algorithmic techniques, can yield valuable biological insights.

Causal regulatory networks help reveal the hidden regulators of gene expression patterns. To facilitate their analysis we established an efficient method for evaluating the significance of the overlap of ternary signals, which generalizes Fisher’s exact test. We used this method to analyze a large-scale causal regulatory network and uncovered new regulators of cardiac hypertrophy.

Metabolic networks help identify novel drug targets. We uncovered structural features of these networks that had been missed by previous researchers, and developed a theoretical framework based on duality for analyzing them in a consistent fashion. We used this theoretical framework to create a new metabolic network for Mycobacterium tuberculosis by algorithmically merging two existing networks, and identified several putative drug targets.

Bio: My research interests lie primarily in the modeling of infectious diseases, both on the molecular level (using approaches from computational and systems biology) as well as on the population level (using approaches from epidemiology and biostatistics). I am particularlly interested in the interactions between science, medicine and policy as they relate to improving patient outcomes, especially in low-income, low-resource settings.

About Jonathan Eisen

I am an evolutionary biologist and a Professor at U. C. Davis. (see my lab site here). My research focuses on the origin of novelty (how new processes and functions originate). To study this I focus on sequencing and analyzing genomes of organisms, especially microbes and using phylogenomic analysis

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