报告题目:  Data integration across omics landscapes
报  告  人:  Dr. Bing Zhang, Vanderbilt University, USA
报告时间: 2011年10月18日上午9:30-10:30
报告地点：生命科学技术学院1号楼105会议室
组织单位：生物统计学与生物信息学系

摘要:
Advancements in high-throughput omics technologies have provided an unprecedented opportunity for biology and biomedical studies. At the same time, advanced technologies have led to an increasing gap between data generation and investigators’ ability to interpret the data. To enable biologically meaningful and efficient analysis of these high-throughput data, we develop data integration approaches around basic molecular and systems biology principles. Specifically, we exploit the information flow from DNA to RNA to protein as defined by the central dogma of molecular biology and the interactions between molecules as defined by network biology to facilitate data integration. In this talk, I will give examples on the application of these approaches to protein identification in shotgun proteomics studies and multidimensional omics data integration in cancer studies.

报告人介绍:

Dr. Zhang received his Ph.D. in molecular genetics from the Shanghai Institute of Plant Physiology, Chinese Academy of Sciences. His postdoctoral research at the University of Tennessee, Knoxville and Oak Ridge National Laboratory focused on bioinformatics and functional genomics. He joined the Department of Biomedical Informatics, Vanderbilt University as an assistant professor since June 2006.

Dr. Zhang's current research interests include systems biology and its application on human cancer studies, gene expression and regulation, and knowledge-guided omics data analysis and interpretation. The long-term goal of the Zhang Lab is to develop systems biology approaches to disease mechanisms, diagnosis, prevention, and therapy.
Shan Cong, Assistant
Department of Bioinformatics and Biostatistics
College of Life Science and Biotechnology
Room 4-323A, Life Science Building
Shanghai Jiaotong University
800 Dongchuan Road, Shanghai, 200240 China
Tel: +86-21-3420-4573
Fax: +86-21-3420-4573
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