学术预告:Imputing dropout events in single cell RNA sequencing data via ensemble learning- www.4066.com

学术科研

学术预告:Imputing dropout events in single cell RNA sequencing data via ensemble learning

发布日期:2019-06-27 发表者:肖尚桃 浏览次数:次

报告题目: Imputing dropout events in single cell RNA sequencing data via ensemble learning

报告人:张晓飞 博士

报告时间:2019628日(周五)15:00

报告地点:逸夫楼C314会议室

摘要:

Imputation of dropout events that may mislead downstream analyses is a key step in analyzing single-cell RNA-sequencing (scRNA-seq) data. We develop EnImpute, an R package that introduces an ensemble learning method for imputing dropout events in scRNA-seq data. EnImpute combines the results obtained from multiple imputation methods to generate a more accurate result. A Shiny application is developed to provide easier implementation and visualization. Experiment results show that EnImpute outperforms the individual state-of-the-art methods in almost all situations. EnImpute is useful for correcting the noisy scRNA-seq data before performing downstream analysis.

报告人简介:

张晓飞,华中师范大学数学与统计学www.4066.com副教授,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。现主持国家自然科学基金面上项目1项、湖北省自然科学基金面上项目1项。曾主持国家自然科学基金青年项目1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 IEEE transactions on Cybernetics IEEE Transactions on Image ProcessingIEEE/ACM Transactions on Computational Biology and BioinformaticsBMC BioinformaticsBMC Genomics等学术期刊发表学术论文30余篇,累计影响因子110左右。

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