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Patrice Davis-Duncan
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Summary Sentence: Computational Health Distinguished Lecture Series: Inferring Host-Pathogen Interactions from Diverse Data Sources, Mark Craven
Full Summary: No summary paragraph submitted.
Mark CravenWhat: Computational Health Distinguished Lecture Series
When: Thursday, March 2, 2017
Time: 2:30 – 3:00PM (Meet and Greet); 3:00PM – 4:00PM (Lecture)
Where: TSRB Auditorium
Speaker: Mark Craven, PhD
Title: Inferring Host-Pathogen Interactions from Diverse Data Sources
Abstract:
Dr. Craven will discuss work in several studies that involve developing and applying predictive methods in order to characterize host-pathogen interactions. In the first study, we are focused on inferring host subnetworks that are involved in viral replication from genome-wide loss-of-function experiments. Although these experiments can identify the host factors that directly or indirectly facilitate or inhibit the replication of a virus in a host cell, they do not elucidate how these genes are organized into the biological pathways that mediate host-virus interactions. We are developing novel computational methods that use a wide array of secondary data sources, including the scientific literature, to transform the measurements from these assays into hypotheses that predict the pathways in the cell that relate implicated genes to viral replication. In the second study, we are applying machine-learning methods to understand how variation in the genome of the HSV-1 virus influences multiple ocular disease phenotypes in a host. In the third study, we are investigating the extent to which risk for various infectious disease phenotypes can be predicted from electronic health records by using machine-learning methods.
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Biosketch:
Mark Craven is a professor in the Department of Biostatistics and Medical Informatics at the University of Wisconsin, and an affiliate faculty member in the Department of Computer Sciences. He is the Director of the Center for Predictive Computational Phenotyping, one of the NIH Centers of Excellence for Big Data Computing. He is also the Director of the NIH/NLM-funded Computation and Informatics in Biology and Medicine (CIBM) Training Program, and a member of the Institute for Clinical and Translational Research, the Carbone Cancer Center, and the Genome Center of Wisconsin.
