Computational prediction of alternative transcription units in prokaryotic genomes

发布者:文明办发布时间:2019-06-27浏览次数:259


主讲人:刘丙强 山东大学教授 博士生导师


时间:2019年6月29日14:20


地点:三号楼332会议厅


举办单位:数理学院


主讲人介绍:山东大学数学学院教授、博士生导师。所在学科为运筹学与控制论,研究方向为组合最优化与生物信息学。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,研究方向为生物信息学。2010年留校任教,2013年任山东大学数学学院副教授,2017年任教授。主要研究方向为利用图与组合优化的模型与理论针对生物信息学问题进行算法设计与数据分析,研究课题包括转录因子结合位点计算预测、表达数据分析、调控网络构建等等。


内容介绍:Identification of transcription units (TUs) encoded in prokaryotes is essential ?to predict the function of unknown genes, annotate the prokaryotic genome and ?construct the transcriptional and translation regulatory networks at the gene ?level. The alternative transcription units (ATUs) are the dynamic TUs from a ?cluster of genes. The identification of ATUs is recognized as a more challenging ?computational problem due to their condition-dependent nature, and the next ?generation sequencing technique provided a good opportunity. We are trying to ?develop a method to predict ATUs in prokaryotes based on RNA-seq data. The ?problem was described as a mathematical programming model, along with the ?integrating of other factors including RNA degradation effect, cross-gene reads. ?We tested the methods with two RNA-seq data on E.coli genome and compared the ?predicted ATUs with experimentally validated ATUs from previous studies. The ?comparison results show that our algorithm can recover the majority of ?previously known ATUs with average precision of 0.70/0.66 and recall of ?0.77/0.79 on two datasets. As the first de novo computational ATU prediction ?pipeline, the new method will facilitate the research on complex mechanism of ?transcriptional regulation, and bring more attention to the function of ?alternative transcription units in prokaryotic genomes.