Radhakrishnan (Krishna) Mahadevan | Associate Professor
BTech (Indian Institute of Technology), PhD (Delaware)
- Department of Chemical Engineering & Applied Chemistry
- Institute of Biomaterials & Biomedical Engineering
Office: Wallberg Building (WB), 200 College Street, Room 326
+1 416 946-0996 (office)
Systems Analysis and Engineering of Biological Processes
Modelling and analysis of metabolic and regulatory networks, bioinformatics and systems biology, engineering biological systems for applications in metabolic engineering, bioremediation, bioenergy and bioprocess optimization.
Recent advances in experimental and computational technologies have enabled the detailed characterization of biological systems. In particular, the molecular components of these systems including the list of genes, proteins they encode, and compounds that interact with these proteins can be determined. This availability of tools to analyze system-wide changes at the level of the genes, proteins, and metabolites has created significant opportunities to understand cellular functions, and to ultimately design processes in a systematic way for applications in industrial and medical biotechnology (e.g. metabolic engineering, bioprocess optimization and control). The research interests of our group involve the development and utilization of dynamic mathematical models of biological systems for improved design, optimization and control.
Genome-scale models of cellular processes
Although detailed models of cellular processes have been constructed in the past, research in this area has attained a new dimension in the last few years due to the development of novel high-throughput experimental techniques for both sensing and manipulating cellular processes at a molecular level. As an example, both steady state genome scale models and smaller dynamic models of metabolism of several industrially important organisms including Escherichia coli have been developed in the past.
Optimization and control of biological processes
Several engineering disciplines (e.g., mechanical, electrical, & chemical) routinely use quantitative models for design and optimization of processes of interest. However, such rational approach to design and optimization has been possible in the life science only recently due to the lack of predictive large-scale models of biological processes in the past. Research activities in our group include the design of dynamic model-driven engineering strategies for biological process optimization and control across different length and time scales (i.e., from microscopic (intracellular) processes to macroscopic (bioreactor) processes).
Perform an automatic PubMed search of this researcher’s publications