一、题目：Data-driven methods for RNA computational biology
二、主讲人：Shi-Jie Chen (陈世杰)
三、时间：2019年11月20日（星期三）下午13：30
四、地点：闻理园A4-218
内容摘要：
RNA molecules play spectacularly versatile roles in living cells.Emerging biomedical advances such as precision medicine and synthetic biology, all point to RNA as the central regulators and information carriers.Furthermore, the ever-increasing database for non-coding RNAs inspire a great variety of RNA-based therapeutic strategies. RNA functions depend on precisely folded RNA structures.However, currently the number of available structures deposited in the structure database such as PDB is only a small fraction of all the structures that we would like to know. This gap has to be closed by computational methods. With the long-term goal of predicting three-dimensional structure from the nucleotide sequence and rational design of RNA-based drugs, we have systematically developed data-driven and data-drive/physics-based hybrid methods for important RNA biology problems such as the prediction of RNA three-dimensional structures from the sequence and metal ion-RNA interactions. I will discuss our recently developed new methods in addressing the above problems and the biomedical applications of these methods.
主讲人简介：
陈世杰教授是美国密苏里大学董事会冠名杰出教授。陈教授任职于密苏里大学物理与天文系、生物化学系、数据科学与信息学研究院。他1987年毕业于浙大物理学专业，获学士学位。后通过李政道先生倡导组织的CUSPEA项目到美国学习；1994年获得University of California-San Diego的物理学博士学位，方向为理论等离子体物理。2012年当选为美国物理学会（APS）Fellow。2018年当选为美国科学促进会（AAAS) Fellow。陈世杰教授是《PLoS-Computational Biology》Associate Editor；国际RNA纳米技术与纳米医学学会创始理事会成员，美国国家卫生研究院NIH和美国国家基金委NSF多个重要项目的主持人，先后在Nature Communications, PNAS, JACS, Annual Review of Biophysics, Nucleic Acids Research等杂志上发表百余篇论文。
研究组网站：http://vfold.missouri.edu/
欢迎广大师生积极参加！联系人：孙婷婷 (物理系)
