报告人：欧阳乐副教授，深圳大学电子与信息工程学院

报告题目：基于图模型的基因网络推断方法

报告时间：2023年9月1日10:00-11:00

报告地点：腾讯会议 ID：707-4850-8649

报告摘要：

The inference of gene regulatory networks (GRNs) is of great importance for understanding the complex regulatory mechanisms within cells. Advances in high-throughput sequencing technologies have provided tremendous opportunities for inferring GRNs via computational approaches. However, existing GRN inference methods are mainly designed for inferring a single network from a single data source, which ignores the commonalities and differences between different networks and the information provided by multiple data sources. In this talk, I will introduce our recent works on GRN inference.

个人简历：

深圳大学电子与信息工程学院副教授，博士生导师。主要从事生物信息学和机器学习等领域的科研和教学工作。广东省珠江人才计划青年拔尖人才、深圳市优青获得者。主持多项国家级和省部级科研项目，已在IEEE TCYB、Bioinformatics、Briefings in Bioinformatics、Pattern Recognition等国际期刊发表SCI论文60余篇。担任Nature Communications、Bioinformatics、 PLoS Computational Biology、 Briefings in Bioinformatics、IEEE JBHI等重要刊物审稿人，AAAI、IJCAI、ICML、NIPS等国际学术会议程序委员会委员。