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演讲摘要：Single‐cell Hi‐C technology is emerging and will provide unprecedented opportunities to elucidate chromosomal dynamics with high resolution. How to characterize pseudo time‐series of single cells using single‐cell Hi‐C maps is an essential and challenging topic. To this end, a powerful circular trajectory reconstruction tool CIRCLET is developed to resolve cell cycle phases of single cells by considering multiscale features of chromosomal architectures without specifying a starting cell. CIRCLET reveals its best superiority based on the combination of one feature set about global information and another two feature sets about local interactional information in terms of designed evaluation indexes and verification strategies from a collection of cell‐cycle Hi‐C maps of 1171 single cells. Further division of the reconstructed trajectory into 12 stages helps to accurately characterize the dynamics of chromosomal structures and explain the special regulatory events along cell‐cycle progression. Last but not the least, the reconstructed trajectory helps to uncover important regulatory genes related with dynamic substructures, providing a novel framework for discovering regulatory regions even cancer markers at single‐cell resolution.
讲者简介：西安电子科技大学计算机科学与技术学院华山准聘副教授，主要方向为三维基因组学、单细胞组学、图表示学习等交叉研究。以第一作者在国际高水平期刊《Advanced Science》、《Nucleic Acids Research》等发表研究论文。担任领域著名期刊Bioinformatics、TCBB等期刊审稿人。主持国家自然科学基金青年项目、参与国家自然科学基金重点项目、面上项目等4项。开发工具CIRCLET入选“2019年度中国生物信息学十大算法”。
第五届中国计算机学会生物信息学会议
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