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山东大学刘丙强教授学术报告

【作者: | 发布日期:2022-04-21 | 浏览次数:

报告题目: Gene Regulation Inference using High Throughput Sequencing Data

告 人:刘丙强

报告摘要:Reconstruction and analysis of transcriptional regulatory networks is a key to understand the intrinsic mechanism of the life. Currently, numbers of challenging questions in this research area need to be answered such as how the TFs regulate genes, how the genes be organized in transcription, and so on. High throughput sequencing data provides unprecedented opportunities to overcome these difficulties. Meanwhile, it also brings new computational and modeling challenges in high-dimensional data mining and heterogeneous data integration. To infer gene expression regulation mechanisms, we developed a series of computational frameworks focusing on several important computational problems including regulatory motif finding, regulon prediction, transcriptional unit prediction etc., both on bacterial and human genomes. These studies provided fundamental knowledge to guide the reconstruction and analysis of transcriptional regulatory networks, improved our understanding of how gene expression is controlled by the underlying regulatory systems, and have promising potentials on the research of regulatory mechanisms underlying complex diseases.

报告人简介:刘丙强,山东大学数学学院教授、博士生导师,副院长。2003年毕业于山东大学数学学院基础数学专业,获学士学位。2010年毕业于山东大学数学学院运筹学与控制论专业,获博士学位。其间于2007年1月至2010年1月赴美国乔治亚大学联合培养。毕业后留山东大学数学学院从事教学科研工作。主要研究方向为利用图与组合优化的模型与理论针对基因表达调控中的系列计算问题进行算法设计与数据分析,包括转录因子结合位点计算预测、转录单元和调节子预测、调控网络构建与分析等。

报告时间: 2022-04-22 700-830

报告地点: 腾讯会议116961853

报告邀请人:张克玉

主办单位:数学学院