应pc加拿大预测准确率概率统计研究所邀请，上海财经大学统计与管理学院吴梦云副教授将于近期访问我校并作学术报告。

报告题目：Integrative clustering of multidimensional omics data

地  点：齐云楼815

时  间：9月14日下午5:00

报告摘要：Clustering analysis has been a critical component of genetic study on complex diseases. For example, the clusters of subjects can serve as the basis for disease subtype identification, risk stratification, as well as many other purposes. With the small sample sizes of genetic profiling studies and noisy nature of omics data, the clustering analysis on a single dataset often leads to unsatisfactory results. In recent profiling studies, a prominent trend is to collect data on multidimensional omics data, including gene expressions as well as their regulators (copy number alteration, microRNA, methylation, etc.) on the same subjects. In our study, we conduct integrative clustering of multidimensional omics data based on the regularized estimation and NCut techniques. Simulations show that the proposed methods have significantly improved clustering accuracy. In the analysis of cancer genomic data, biologically sensible findings different from the alternatives are made.

报告人简介

吴梦云，上海财经大学统计与管理学院副教授。2013年获得中山大学概率论与数理统计博士学位，并与2016年8月至2018年7月在耶鲁大学生物统计系进行博士后研究。主要研究方向为高维数据变量选择、网络模型及整合分析等。目前，已在The Annals of Applied Statistics、Statistics in Medicine、Briefings in Bioinformatics、Genetic Epidemiology、Genomics等期刊发表多篇学术论文。国际统计学会当选会员（Elected Member, International Statistical Institute ISI），主持并完成了国家自然科学青年基金项目。

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