交通大學、清華大學 統計學研究所 專題演講 題　目：以網路生物學策略來解析生物醫學的複雜問題 主講人：林仲彥博士 (中央研究院資訊科學研究所) 時　間：99年3月12日(星期五)上午10:40-11:30 (上午10:20-10:40茶會於交大統計所429室舉行) 地　點：交大綜合一館427室 Abstract In past few years, our team put focus on following fields via IT innovations to decipher biological secrets hidden inside complex phenomena. We have implemented a statistical model into our protein interaction database for validation of two-hybrid assays of Helicobacter pylori, and prediction of putative protein interactions not yet discovered experimentally. By this approach, we can compare the interacting network of various strains with different virulence to decipher the secret between hosts and pathogens (http://dpi.nhri.org.tw/hp/, Bioinformatics 2005). Using the more sophisticated statistical method with expression profile, we integrated a database named as flydpi for the interactome of Drosophila Melanogaster (http://flydpi.nhri.org.tw, BMC Bioinfo, 2006). Based on the evolutionary strategy, the predicted human protein-protein interactions associated with confidence scores are derived from six eukaryotic organisms – rat, mouse, fly, worm, Arabidopsis and baker's yeast (BMC Bioinformatics, 2007). And we also constructed a topological analyzer for complex network named as Hubba – Hubba (http://hubba.iis.sinica.edu.tw, NAR, 2008) to identify the essential nodes and the relationships among them. Moreover, the platform for network comparison will be completed soon to assist us for telling the conserved network motifs inside various networks. Objectives of our work are to improve our understanding of the puzzle during development stage, carcinogenesis and infectious mechanism, and to furthermore introduce a new paradigm for the diagnosis and treatment of human disease to revolutionize current medical services delivered. 敬 請 公 佈 歡 迎 參 加 --

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