报告题目： Network-based Phenome -Genome Association Analysis

报告人： Dr. Rui Kuang　　　 University of Minnesota Twin Cities

时 间： 2013年7月22日（星期一）上午10点

地 点：动物所 C101会议室 

联系人：王秀杰（64806590）

报告摘要：

In the past decade, genome-wide studies of disease-gene associations enabled by the high-throughput genomic technologies revealed many disease causal genes. Driven by the determined associations, a promising next step is to perform large-scale association analysis between all genes and the complete collection of phenotypes (phenome). In this talk, I will introduce our research work on three aspects of phenome-genome association analysis, 1) disease gene prioritization which determines candidate disease genes for a single query disease phenotype; 2) phenome-genome association prediction which reconstructs the complete phenotype-gene associations; and 3) module-based phenome-genome analysis which co-clusters phenotypes and genes, and simultaneously identifies associations between the detected phenotype clusters and gene clusters. We designed subnetwork-based label propagation, bi-random walk and regularized non-negative matrix tri-factorization for the three problems, respectively. Promising results were observed in the cross-validation experiments on the disease phenotype-gene associations in OMIM.

报告人简介：

Dr. Rui Kuang is an assistant professor in computer science and engineering at the University of Minnesota Twin Cities. His research interests span computational biology, machine learning and biomedical/health informatics. He specializes in machine learning algorithms and network analysis methods for understanding the molecular characteristics of disease phenotypes from high-throughput genomic sequence data and array-based expression data. His current projects center around cancer genomics, disease phenome-genome association, and analysis of protein structures and functions. Dr. Kuang is a recipient of NSF career award. He received his PhD from Columbia University, MS from Temple University and BS from Nankai University, all in computer science.