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Computational methods to elucidate chromatin topological structures using 3D genomic maps
浏览次数:日期:2020-10-29编辑:信科院 科研办

报告人:张世华研究员,中国科学院数学与系统科学研究院

报告时间:20201030 下午3:30

报告地点:信息科学与工程学院 432

报告摘要:The chromosome conformation capture (3C) technique and its variants have been employed to reveal the existence of a hierarchy of structures in three-dimensional (3D) chromosomal architecture, including compartments, topologically associating domains (TADs), sub-TADs and chromatin loops. In this talk, I am going to introduce three methods on deciphering 3D genomic maps: (1) a mixed-scale dense convolutional neural network model (HiCMSD) to enhance low-resolution Hi-C interaction map for deciphering biologically significant multi-scale topological structures; (2) a generic and efficient method to identify multi-scale topological domains (MSTD), including cis- and trans-interacting regions, from a variety of 3D genomic datasets; (3) a powerful and robust circular trajectory reconstruction tool CIRCLET without specifying a starting cell for resolving cell cycle phases of single cells by considering multi-scale features of chromosomal architectures.

 

报告人简介:张世华,中国科学院数学与系统科学研究院研究员、中国科学院随机复杂结构与数据科学重点实验室副主任、中国科学院大学岗位教授。主要从事优化、统计、机器学习与生物信息学交叉研究,主要成果发表在Advanced Science、National Science Review、Nature Communications、Nucleic Acids Research、Bioinformatics、IEEE TPAIM、IEEE TKDE、IEEE TFS、AoAS等杂志。目前担任BMC Genomics等杂志编委。曾荣获中国青年科技奖、国家自然科学基金优秀青年基金、中组部万人计划青年拔尖人才、全国百篇优秀博士论文奖、中国科学院卢嘉锡青年人才奖等。


联系人:骆嘉伟