Our research group uses a combination of interdisciplinary approaches including chemical engineering, synthetic biology, systems biology, molecular biology, microbiology, metabolic engineering and computational biology to address key global challenges including medical and energy needs. We are interested in adopting an integrated mathematical modeling and experimental approach to investigate fundamental and medically relevant issues such as understanding the molecular mechanisms responsible for antibiotic and antiviral resistance, and for developing “next-generation smart antimicrobials” by rationally engineering novel therapeutics that target essential bacterial/viral genes in a potentially resistance-free manner. We study genetic regulatory networks that control propagation of infectious diseases such as Hepatitis C, with the goal of discovering novel drug targets for therapy. Using synthetic biology tools we design, construct and engineer modular synthetic genetic devices that can achieve higher-order biological computation, for variety of biotechnological and bioenergy applications. To this end, we engineer biological parts such as transcription factors, promoter sequences, receptors, feedback loops, and regulatory RNA to build complex genetic networks that can be used to optimize cellular machinery for production of bio-fuels and pharmaceuticals, and for gene therapy applications. Using these genetic devices, we apply systems biology approaches to understand functioning of complex genetic networks and to build rules to manipulate such networks.
“Role of intracellular stochasticity in biofilm growth. Insights from population balance modeling,” 2013, PLoS ONE 8(11): e79196. doi:10.1371/journal.pone.0079196.
“Antagonistic self-sensing and mate-sensing signaling controls antibiotic-resistance transfer,” 2013, PNAS, 110(17), 7086-709.
“Hepatitis C viral kinetics: the past, present and future,” 2013, Clinics in Liver Disease, 17 (1): 13-26Read More