北京大学定量生物学中心
学术报告
题 目: Uncovering metabolite-mediated cell communications by single-cell RNA-Seq
报告人: Kaifu Chen, Ph.D.
Associate Professor, Harvard Medical School
Director of Computational Biology Program, Cardiology Department, Boston Children’s Hospital
Broad Institute of MIT and Harvard
Dana-Farber Harvard Cancer Center
时 间: 4月17日（周一）9:00-10:00
地 点: Zoom线上
会议号：910 9636 7823
密码：cqb2023
https://zoom.us/j/91096367823?pwd=ZUVOYnZ1SkxQY1Z1QkllZzRib3dPUT09
主持人: 曾泽贤 研究员
摘 要:
In this seminar, Dr. Chen will introduce investigation of metabolite-mediated intercellular communications based on single cell RNA-seq data. They recently developed the MEBOCOST algorithm that infers cell-cell communication events in which metabolites secreted by one cell travel to interact with sensor proteins of another cell. Dr. Chen will introduce application of MEBOCOST to investigation of atherosclerosis and thermogenesis, in which they successfully recaptured many reported metabolic communications and further, revealed new mechanisms experimentally verified to play critical roles. Their software to run the MEBOCOST algorithm is available at https://github.com/zhengrongbin/MEBOCOST for the community to use for free.
报告人简介：
Kaifu received undergraduate training in Biophysics at the Nankai University and Ph.D. training in Genomics in the lab of Dr. Jun Yu at the Beijing Institute of Genomics, Chinese Academy of Sciences. He performed bioinformatics research at his postdoctoral stage in the lab of Dr. Wei Li at the Baylor College of medicine. He then founded his bioinformatics lab at the Houston Methodist Hospital and Weill Cornell Medical College of Cornell University as an Assistant Professor, and later became the Director of their Center for Bioinformatics and Computational Biology. He finally moved to Harvard Medical School at Boston Children’s Hospital and is now leading their Computational Biology Program. He is also affiliated with the Broad Institute and the Dana-Farber / Harvard Cancer Center. Kaifu’s major research interest is in computational modeling of cell identity regulation.
