主 講 人：胡耀華

主辦單位：數學與大數據學院

講座時間：2019年11月8日  17：00-18：00

講座地點：知津樓C303

內容簡介：

Inferring gene regulatory networks from gene expression data is an arduous challenge in biology especially in higher organisms, which is found to have a special structure of transcriptional factory in [Science 2010] and [Nature 2010]. In this talk, we will consider a mix sparse optimization model with this special structure, that is, sparsity structures at intra-group and inter-group levels are considered simultaneously. We will propose a nonconvex regularization method, as well as a first-order iterative algorithm, and present its consistence theory and convergence theory. The applications of mix sparse optimization will facilitate biologists to study the transcriptional factory structure of gene regulation networks for higher model organisms in a genome-wide scale.

主講人簡介：

胡耀華，江西吉安人，先后于浙江大學獲得學士、碩士學位，香港理工大學獲得博士學位，現任深圳大學數學與統計學院副教授。主要從事連續優化理論、算法和應用研究，主持國家自然科學基金2項，省市級科研項目5項。在SIAM Journal on Optimization，Journal of Machine Learning Research等國際期刊上發表二十篇余學術論文，參與開發多個生物信息學工具包/網頁服務器。2015年深圳市海外高層次人才“孔雀計劃”C類人才，2016年廣東省計算數學優秀青年論文特等獎，2017年深圳市南山區“領航人才”。