Recent advances of single-cell and spatial sequencing technologies provide an unprecedented opportunity for probing underlying intercellular communications that often drive heterogeneity and cell state transitions in tissues. I will introduce our integrated method CellChat for systematic inference and analysis of cell-cell communication by integrating scRNA-seq data and prior knowledge of the interactions between signaling molecules. Then I will show how we can 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 can infer spatially resolved cell-cell communication and high-order interactions that reveal how cells and signals coordinates together for function.

金锁钦, 武汉大学数学与统计学院教授, 博士生导师, 国家级青年人才。2016年博士毕业于武汉大学, 随后在美国加州大学尔湾分校从事博士后研究。主要从事数学、人工智能与生物医学交叉研究, 在单细胞/空间组学数据的数学建模和智能挖掘、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等方面开展了系列研究。研究成果发表在Nat. Commun., Cell Genomics, Nat. Neurosci., Nat. Protoc., Genome Biol.等学术期刊上, 单篇文章最高引用达7000余次, 获2024国际基础科学大会"前沿科学奖"。