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Speaker: Elebeoba E. May
Associate Professor, Department of Biomedical Engineering
University of Houston

Computational Systems Biology and the Dynamics of Pathogenesis

Tuesday, October 2, 2012
4:00 PM  to 5:00 PM

280  Brown College
Rice University
6500 Main St
Houston, Texas, USA

Modeling and simulation are critical tools in the mathematical, and engineering sciences and enable the testing, verification, and exploration of the behavior of physical systems. With the proliferation of multi-omic data biomedical scientists are increasing their use of mathematical tools for data analysis and integration, however the use of simulation tools is an important and not yet fully realized complement to empirical studies. Scientific areas of high consequence in advancing global health initiatives can be challenging to investigate experimentally due to controversy (e.g. human testing of new vaccines or therapeutics), bioengineering challenges (e.g. regeneration of damaged neurons), or technological limitations (e.g. multiscale observations of mechanisms that regulate immunopathogenesis). By leveraging high performance computing environments in combination with scientific simulation tools we can advance the development of computational bioscience platforms to explore biological phenomena and biomedical systems that are currently difficult to investigate using empirical methods alone. In our work we use methods from the field of electrical engineering to develop computational tools for biological modeling and analysis. We have developed BioXyce, an electrical circuit-based systems biology simulation platform, and demonstrated its use in studies of biochemical pathways involved in Mycobacterium tuberculosis (Mtb) and Francisella tularensis infection and immune response. We are creating integrated experimental and computational platforms to model and study biochemical systems involved in immune response, pathogen survival, and persistence using in vitro and in vivo models of infection. Developing methods and tools for simulation-based exploration of biomolecular systems will facilitate the use of computational systems biology to advance biomedical challenges in areas such as: development of novel small molecule therapies for antibiotic-resistant bacteria, identification of mechanisms that enable latent infections, and prevention of failures in immune mechanisms that enable reactivation.

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