alexa Jeffrey Skolnick | Center for the Study of Systems Biol
ISSN: 2153-0602

Journal of Data Mining in Genomics & Proteomics
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Jeffrey Skolnick

Jeffrey Skolnick Jeffrey Skolnick
Director
Center for the Study of Systems Biology
Georgia Institute of Technology
United states
Biography

Jeffrey Skolnick is the Director of the Center for the Study of Systems Biology in the School of Biology at the Georgia Institute of Technology. He is also the Mary and Maisie Gibson Chair in Computational Systems Biology and a Georgia Research Alliance Eminent Scholar in Computational Systems Biology. He attended graduate school in Chemistry at Yale University, receiving a Ph.D. in Chemistry in polymer statistical mechanics. He then held a postdoctoral fellowship at Bell Laboratories. Next, he joined the faculty of the Chemistry Department at Louisiana State University, Baton Rouge. Then, he moved to Washington University, where he was subsequently appointed Professor of Chemistry. There he was also Director of the Institute of Macromolecular Chemistry at Washington University. He joined the Department of Molecular Biology of the Scripps Research Institute, where he held the rank of Professor. Among his awards is Southeastern Universities Research Association (SURA), Distinguished Scientist Award an Alfred P. Sloan Research Fellowship and he is a Fellow of the American Association for the Advancement of Science, the Biophysical Society, and the St. Louis Academy of Science. He is the author of over 360 publications and has served on numerous editorial boards including the Israel Journal of Chemistry, Peer J, Biology Direct, Biophysical Journal, Biopolymers, Proteins, and the Journal of Chemical Physics. He is also a cofounder of an early stage structural proteomics company, GeneFormatics, and his software has been commercialized by Intellimedix and Tripos.

Research Interest

Dr. Skolnick’s current research interests are in the area of computational biology and bioinformatics. He has developed and applied approaches to proteomes for the prediction of protein structure and function, the prediction of small molecule ligand-protein interactions with applications to drug discovery and the prediction of off-target uses of existing drugs, fundamental studies on the nature and completeness of protein structure space and the exploration of the interplay between protein physics and evolution in determining protein structure and function, prediction of protein-protein and protein-DNA interactions, cancer metabolomics and molecular simulations of cellular processes.

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