报 告 人:金锁钦 副教授(武汉大学数学与统计学院)
报告时间:2022年9月27日(星期二)上午9:30-10:30
报告地点:腾讯会议:289-801-087
邀 请 人:刘锐教授、陈培副教授
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数学学院
2022年9 月22日
报告摘要:Recent advances of single-cell technologies, in particular single-cell RNA sequencing and spatial imaging, provide an unprecedented opportunity for probing underlying intercellular communications that often drive heterogeneity and cell state transitions in tissues. In this talk, I will show our recent efforts in modeling and analyzing cell-cell communication from the high-throughput sequencing data. We developed an integrated method for systematic inference and quantitative analysis of cell-cell communication by integrating scRNA-seq data and prior knowledge of the interactions between signaling molecules. I will show how we can quantitatively build and analyze cell-cell communication networks in an easily interpretable way by applying systems biology and machine learning approaches. Furthermore, by leveraging spatial information from spatial transcriptomics, we developed a computational approach for inferring niche programs that capture the underlying cell-cell communication patterns and reveal how cells and signals coordinates together for function.
报告人简介:金锁钦,武汉大学数学与统计学院副教授。研究方向是计算生物学、生物信息学和大数据分析,在发展数学的理论与方法应用于解决生物医学前沿科学问题、单细胞等生物医学大数据的数学建模和计算挖掘等方面开展了系列研究。研究成果发表于Nature Communications, Nature Neuroscience, Genome Biology, Cell Reports, SIAM Journal on Applied Mathematics等领域知名期刊上。