学术讲座

学 术 讲 座

主题:Integrated and systematic views of regulatory

          DNA motif identification and analyses

主讲人:Qin Ma (美国南达科塔州立大学助理教授)

时间20170522 (周一)下午 3:30-5:00

地点:我校津南校区计算机与控制工程学院(信息东楼)328

AbstractTranscription factors are proteins that bind to specific DNA sequences and play important roles in controlling the expression levels of their target genes. Hence, prediction of transcription factor binding sites (TFBSs or motif for short) provides a solid foundation for inferring gene regulatory mechanisms and building regulatory networks for a genome. Motif identification and analyses are important and have been long-standing computational problems in bioinformatics. Substantial efforts have been made in this field during the past several decades. The bottleneck, however, is the lack of robust mathematical models, as well as efficient computational methods for motif prediction to make effective use of massive data sets in the public domain (e.g., ChIP-seq).

 

In this talk, I will present an integrated platform, DMINDA 2.0, which contains: (i) five motif prediction and analyses algorithms, including a de-novo genome-scale prediction algorithm a phylogenetic footprinting framework; (ii) 2,125 species with complete genomes to support the above five functions, covering animals, plants, and bacteria; and (iii) regulatory systems prediction and visualization.

 

Biography马勤, 博士毕业于山东大学数学学院, 于美国佐治亚大学徐鹰老师实验室进行博士后研究。目前为美国终身, 组建了内首个生物信息学验室,主要从事大规析和相应的在国内外的重要期刊上表论文45 篇(25作者者论文),包括Bioinformatics, Nucleic Acids Research, Briefings in Bioinformatics等国际著名学术期刊应邀在国物信息学和国内外名大学做学术报30余次,研究果被 450 为国际知名生物信息学期 BMC Genomics》与Mathematical Biosciences并于2016年受邀加入美国 NSF 重点项目基金的评审委员


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