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Jin Wang

Jin Wang
Assistant Professor (Chemistry and Physics)
B.S., (Physics) 1984, Jilin University, China;
Ph.D. (Astrophysics) 1991, University of Illinois;
Post Doctor Research Associate (Chemistry and Biological physics ), 1991-1996, University of Illinois;
Guest Scientist, 1996-1997, National Institutes of Health;
Vice President and Senior Analyst, 1997-2005, Citibank;
Adjunct Professor (Physics and Credit Management), 1997-present, Jilin University, China;
Adjunct Professor (Chemistry), 1999-2004, SUNY Stony Brook;
Adjunct Professor, 2002-present, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences;
National Science Foundation Career Award, 2005.

Phone: (631) 632-1185; Fax: (631) 632-7960;
E-mail: jin.wang.1@stonybrook.edu
Publications


Physics and Chemistry of Biomolecules, Cellular Networks and Single Molecules

The main focus of my research is on the study of the fundamental mechanism of biomolecular folding and recognition, especially protein folding and protein-protein/protein-DNA interactions. Using modern statistical mechanics, molecular simulations and empirical information from protein database, energy landscapes of protein folding and recognition can be mapped. By further studying the detailed structure correlations of the landscape, the fundamental questions such as nucleations and nature of transition state ensemble can be answered for different proteins and biomolecular recognition complexes. The results of the study can be compared with the experiments. The energy landscape description of protein folding and recognition will also provide insight of new algorithms of structure prediction and drug design.

I am also interested in the study of the underlying principles of the cellular networks. In particular, I am interested in the nature of the robustness of the cellular networks in the noisy fluctuating environments. I am also interested in understanding and quantifying the dynamics and pathways of the cellular networks. These studies should lead to optimal design and evolution of the networks.

Another focus of my study is on the reaction dynamics in complex environments, specifically biomolecular reactions and interactions where the reaction happens in a relatively fast or comparable time scale relative to the environmental fluctuations. A path integral formalism is developed for the full treatment of the problem. Potential application of this method includes electron transfer in proteins, ligand binding, reaction dynamics in complex solvents.

I am also interested in the study of single molecule reaction dynamics. The single molecule detection provides us detailed picture of molecular reactions without ensemble average. It is also a sensitive probe to the local environments. It can help us to pin down the reaction pathways. Since the single molecule has only one sample, the statistical fluctuations normally ignored under the situation of large samples may not be neglected. Quantitative study of the statistics of single molecule reaction dynamics is very necessary and underway in order to understand the whole picture.

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