Prasad

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• Professor



Department of Chemical Engineering
University of Delaware
Newark, Delaware 19716

302-831-2879
302-831-1048 fax

dhurjati@che.udel.edu


" Our current research in “Biosystems Modeling and Bioinformatics” is built on two decades of accomplishments in biotechnology and the application of knowledge-based expert systems for process fault diagnosis. In biotechnology, our research has resulted in a better understanding of microscopic and macroscopic variables that influence the kinetics of genetically engineered microorganisms. We have investigated different promoters, specialized ribosome systems, microbial hosts, and bioreactor conditions, for the improved production of active proteins. We have collaborated with the Pasteur Institute in Paris to examine the effects of gene sequence on inclusion body formation and also collaborated with DuPont to construct genetically engineered cells that emit light when exposed to pollutants. A second area of major research contributions is in the application of knowledge-based expert systems for on-line fault diagnosis. In a joint project with Foxboro and DuPont, our research group pioneered the first industrial application of an expert system (FALCON), for fault diagnosis in a commercial-scale process. Dynamic simulations and the integration of qualitative domain knowledge with quantitative knowledge from mathematical models were central to this project. A common underlying theme in our work in both biotechnology and fault diagnosis has been the use of dynamic mathematical models, qualitative and quantitative domain knowledge, and artificial intelligence approaches for data interpretation and knowledge integration. The introduction of a gene into an organism perturbs it at many levels of cellular hierarchy. Genomic, Transcriptomic, Proteomic and Metabolic data provide insight into the regulatory and metabolic effects of such gene manipulations at the whole cell level. Our current research combines modeling approaches with knowledge-based data analysis strategies to convert the massive amounts of such bioinformatic data into knowledge. "