Past Event: Oden Institute Seminar

Leveraging computational models of signal transduction and high content data for uncovering molecular underpinnings of heart valve disease

Daniel Howsmon , Postdoctoral fellow, Willerson Center for Cardiovascular Modeling and Simulation, UT Austin

Abstract

Disease of the heart valve are currently treated surgically with either repair or replacement strategies. Although repair strategies are preferred, they often fail prematurely due to the dynamic remodeling and signaling of living tissue. In order to understand the mechanisms of heart valve remodeling in disease scenarios, we use an integrated approach that leverages high content biological experiments with computational models of signal transduction. The ultimate goal of this work seeks to integrate these signal transduction models within a larger multiscale framework of specific heart valves to better understand the remodeling processes that occur in response to disease and predict optimal combinations of surgery and pharmaceutical interventions for different valve diseases. Bio: Daniel P. Howsmon, PhD, is currently a postdoctoral fellow with the Willerson Center for Cardiovascular Modeling and Simulation at the Univ. of Texas at Austin. His research interests lie in using mathematical models and systems theory to shed light on complex biomedical problems and ultimately advance healthcare. He received his PhD in chemical and biological engineering from Rensselaer Polytechnic Institute in 2017 and BS degrees in both chemical engineering and biochemistry from Texas A&M Univ. in 2012.