题 目：Computational Systems Biology: Research Opportunities & Applications for Post-genome Bioinformatics 主讲人：Prof. Jake Chen Indiana University School of Informatics & Purdue University School of Science Dept of Computer and Information Science Indianapolis, IN 主持人：颜光美 教授 中山大学副校长 时 间：2007年7月4日（周三）15：00 地 点：中山大学北校区永生楼四楼
简介：Jake Chen joined the faculty as a joint appointment between the department and the School of Informatics in 2004. He conducts active research in the area of bioinformatics, scientific data management and data mining, functional genomics, proteomics, and systems and network biology. Since 2002, he has successfully obtained funding from institutional, foundation, federal, and international sources as principle investigator (PI) or co-PI, bringing in more than 10 grants and combined value of $7.2 million to support research and education efforts in large interdisciplinary research teams. He has authored or co-authored more than 30 peer-reviewed articles in scientific journals, conference proceedings, or academic books. Each year, he serves on several international conference program committee in bioinformatics, chairs or co-chairs high-quality international conferences and workshops in his field, reviews research papers submitted to top journals in the field of bioinformatics, and gives many invited bioinformatics and database related seminars and lectures worldwide to disseminate scientific discovery methods and results. He is an IEEE senior member and chairs of several local,regional, and national professional organizations edicated to bio-computing. Dr. Chen earned his PhD in Computer Science and Engineering from the University of Minnesota in 2001. 欢 迎 参 加！ 医学科学处 2007年7月2日 Abstract:
With the recent progress in high-throughput technologies and bioinformatics, researchers can determine to what extent external or internal stimulus of the cell affects the expression of thousands of genes and proteins. Molecular network biology is an emerging area at the interface between bio-computing and post-genome biology, which aims to study the relationships and interactions between various entities of a biological system through bioinformatics methods. The global insight can lead to the understanding how genes/proteins are organized in pathways in order to respond to genetic or environmental changes. It also develops researchers to identify novel therapeutic or diagnostic strategies.
In our group (http://bio.informatics.iupui.edu/), we developed an ontology-driven network-enabled framework for molecular systems biology research and applications. This framework consists of the following three elements: (1) analyzing experimental “Omics” (including genomics and functional genomics data) or curated text mining data to identify differentially expressed proteins in different genetic or environmental conditions; (2) integrating “Omics” results and gene functional categories into protein-protein interaction networks; (3) visualizing molecular sub-networks to identify biological hypothesis. I will use two research case studies, one for Alzheimer’s disease and the other for Ovarian Cancer, to show how the framework could be applied to generate novel biological insights. The role of bio-computing in computational systems biology applications will also be discussed.