(大数据时代的转录组分析)

邢毅博士

美国加州大学洛杉矶分校生物信息专业副教授（终身职位）

The recent advent of the high-throughput RNA sequencing (RNA-seq) technology has provided a powerful tool for transcriptome-wide measurements of mRNA isoform complexity at an unprecedented resolution. By generating massive amounts of sequence reads from a given RNA sample, researchers can reveal the identity and quantify the abundance of mRNA isoforms across the entire transcriptome. Large consortium projects are generating RNA-seq data on tens of thousands of samples along with a wide variety of other genomic and phenotypic measurements. However, the enormous potential of these large, complex datasets cannot be fully realized without the development of methods for discovering patterns and generating biological insights from big transcriptome and genome data. In this talk, I will discuss our recent efforts in developing computational and statistical methods for elucidating transcriptome isoform complexity and post-transcriptional RNA regulatory networks using massive RNA-seq datasets.

A Brief Biography

邢毅博士现任美国加州大学洛杉矶分校(UCLA) 微生物、免疫学与分子遗传学系副教授（终身职位）, UCLA生物信息学博士培养项目主任(program director) 。 在转录组分析， RNA可变剪切和转录后调控网络的生物信息学和基因组学研究作出了重大和原创性的工作，发展了一系列被广泛使用的计算生物学算法和工具。 发表学术论文70篇，共被引用约4800次，H-index 34。 曾获著名的斯隆基金会(Sloan Foundation)和10美分活动基金会(March of Dimes Foundation)的青年科学家奖。

讲座时间：3月30日中午12点半   地点：济事楼308（iLab@TongjiU）