The overarching goal of this project is to provide a theoretical and computational framework for modeling and control of genetic regulation to generate effective therapeutic strategies for genetic diseases such as cancer. The accomplishment of such intervention in genetically pathological cells, such as cancer cells, would be a major step in the transformation of medicine to a mathematically grounded engineering discipline based on dynamic molecular interaction. The education goal of this project is to enhance the quality education for engineering students at PVAMU and to increase the number of African-American students pursuing careers in computational and systems biology. Three undergraduate students will be supported by this project each year to work on the research. In addition, many students will be impacted by a new course and several enhanced courses.
The interdisciplinary nature of this project promises to foster crossfertilization of ideas between electrical engineering and systems biology through research and education. The project aims to model drug effects on gene regulation using hybrid systems and infer their targeted genetic regulatory networks in terms of their complex nature - in regard to network dynamics, robustness and sensitivity - thereby designing better intervention strategies. Instead of traditional techniques, such as microarrays that provide a snapshot of an aspect of the system at one time point, the dynamics of tumor cell response to drugs can be quantitatively characterized through a multi-dimensional examination of the cells' responses through drug perturbation to test different combinations of cell type, reporters, and drugs/dosages, augmented by a system identification and control theoretical approach aiming to better understand genetic regulatory network behavior in order to design effective therapeutic strategies.
