George V Popescu is an Assistant Research Professor at the Institute for Genomics, Biocomputing and Biotechnology and an adjunct faculty at the Biochemistry, Molecular Biology, Entomology and Plant Pathology department. Over the past 15 years he has contributed significantly to major genomics and proteomics projects, first as a postdoctoral research associate and later as a senior scientist. He started his research career in data analysis and information engineering. At doctoral level he specialized in computer modeling and simulation, graduating with a thesis elaborated from research contributions in an NSF sponsored biomedical project. His research experience was significantly broadened at the IBM TJ Watson Computer Science Department where he has worked, from 2001 to 2004, in research projects on network modeling, system analysis and optimization. His education was completed between 2004 and 2006 with a postdoctoral training stage in the laboratories of Dr. Michael Snyder and Dr. Sherman Weissman at the Center for Excellence in Genomic Sciences at Yale University. Here he contributed to projects on chromosomal copy number variation, SNP identification and association, DNA methylation pattern analysis, signaling networks inference as well as to the development of novel high-throughput protein microarray assays for protein interaction networks prediction. A significant contribution was the development of a new method for estimation of chromosomal breakpoint’s genomic coordinates and for detection of copy number variation from comparative genomic hybridization (CGH) data. Other key contributions at Yale MCDB were the optimization and development of protein micro-array designs and the analysis of protein-protein interactions to identify signaling networks in plants.
His recent work focuses on predicting biological system’s behavior under non-stress or stress conditions using the systems biology models of immune response circuitry. In an ongoing NSF-MCB project, he investigates the role of controlled proteolysis in signaling circuits that enable plants to withstand oxidative stress. He analyzes how two oligopeptidases TOP1 and TOP2 contribute to the redox proteome phenotype. His work uncovered new information on the impact of TOP1/TOP2 on the composition of the Cys-oxidized proteome in the early stages of the ETI and in redox signaling.