报告人： 张世华博士副研究员中国科学院数学与系统科学研究院 运筹学与生物信息学

报告内容简介：

       Recent technology has made it possible to simultaneously perform multi-platform genomic profiling of biological samples, resulting in so-called “multi-dimensional genomic data”. Such data provide unique opportunities to study the coordination between regulatory mechanisms on multiple levels. However, integrative analysis of multi-dimensional genomics data for the discovery of combinatorial patterns and clinical prognostic analysis is currently lacking. Here, I will briefly survey our recent progresses in this direction, and particularly I will introduce an application of integrating clinical observations and gene expression data on the prognostic abilities of different cancer subtypes. We found that (1) gene expression profiles and clinical features show different prognostic power for the five breast cancer subtypes; (2) gene expression data of the normal-like subgroup contains more valuable prognostic information and survival associated contexts than the other subtypes, and the patient survival time of the normal-like subtype is more predictable based on the gene expression profiles; and (3) the prognostic power of many previously reported breast cancer gene signatures increased in the normal-like subtype and reduced in the other subtypes compared with that in the whole sample set.  

时间：2014年4月13日（星期日）下午 3:00-4:30

地点：8797威尼斯老品牌二楼会议室

邀请人：郭安源

欢迎全院师生参加!