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Statistical Mechanics-Based Methods for Identifying Disease Genes from Biomolecular Networks
发布时间:2017-05-26     来源:太阳成集团tyc4633   分享到:

Statistical Mechanics-Based Methods for Identifying Disease Genes from Biomolecular Networks

 

 

报告人:Dr. FangXiang Wu

报告地点:太阳成集团tyc4633四层报告厅

报告时间: 9:00-10:30

报告日期:2017年5月26日

主办单位:太阳成集团tyc4633  生物大数据计算研究团

It is well known that a complex disease stems from the malfunctions of some biomelcular networks which control the pathogenesis of the complex disease. Disease genes can be viewed as special nodes in biomolecular networks and are not randomly distributed (located) from existing evidences. The identification of disease genes is critical towards the understanding of complex diseases. We formulated identifying disease genes from a biomolecular network as finding the most possible configuration of the network. Borrowing from statistical mechanics, we employed the Boltzmann distribution to compute the probability of configurations of a network while adopting the Ising model to define the network energy. In this talk, I will present some of our recent results for identifying disease genes from biomolecular networks based on our proposed statistical mechanics-based methods.

 

 

Biography

 

Dr. FangXiang Wu received the B. Sc. degree and the M. Sc. degree in applied mathematics, both from Dalian University of Technology, Dalian, China, in 1990 and 1993, respectively, the first Ph.D. in control theory and its applications from Northwestern Polytechnical University, Xi’an, China, in 1998, and the second Ph.D. in bioinformatics and systems biology from University of Saskatchewan, Saskatoon, Canada, in 2004. He worked as a post-doctorial fellow with Laval University Medical Research Center, Quebec City, Quebec, during 2004-2005.

 

Dr. Wu is a full professor of the Department of Computer Science, Division of Biomedical Engineering and the Department of Mechanical Engineering at the University of Saskatchewan, Canada. He is also a guest professor of 1000 Talents Program in Central South University. His current research interests include Machine learning in bioinformatics, Big biological data analytics, Biomolecular network analytics, Complex network controllability and observability, Brain images and brain networks, and Nonlinear biodynamic analytics. He has published more than 260 technical papers in refereed journals and conference proceedings.

 

Dr. Wu is serving as the editorial board member of four international journals (including Scientific Reports), the guest editor of many international journals, and as the program committee chair or member of several international conferences. He has also reviewed papers for many international journals. He is a senior member of IEEE and a registered Professional Engineer in Canada.