报告题目：Imputing dropout events in single cell RNA sequencing data using machine learning

报告时间：2021年7月27日，星期二，下午2:30-5:30

腾讯会议ID：955 215 028

会议链接：https://meeting.tencent.com/s/d7cfolbCjNCF

报告人：张晓飞教授，华中师范大学

报告摘要：

Single-cell RNA sequencing (scRNA-seq) methods make it possible to reveal gene expression patterns at single-cell resolution, paving a new way for understanding of the function of individual cells in the context of microenvironment. Due to technical defects, dropout events in scRNA-seq will add noise to the gene-cell expression matrix and hinder downstream analysis. Therefore, it is important for recovering the true gene expression levels before carrying out downstream analysis. In this talk, I will present our recent studies for recovering gene expression for scRNA-seq by imputing the dropout events.

报告人简介：

    张晓飞，男，博士。华中师范大学数学与统计学学院教授，博士研究生导师。主要从事基于机器学习方法的大规模生物医学组学数据挖掘研究。已主持国家自然科学基金项目2项，参与国家重点研发计划“精准医学研究”重点专项1项，参与国家自然科学基金重点项目1项。已在Bioinformatics、 Briefings in Bioinformatics、IEEE Transactions等学术期刊发表论文40余篇，开发应用软件包20余个。