学术报告

荔园杰出学者讲座第二十二期:Spatiotemporal Learning of High-dimensional Cell Fate

时间:2024-03-14 12:40

主讲人 聂青 教授(加州大学尔湾分校) 讲座时间 2024年04月12日上午10:00-11:00
讲座地点 深圳大学粤海校区汇星楼一楼一号教室 实际会议时间日 12
实际会议时间年月 2024.4

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荔园杰出学者讲座第二十二期

讲座题目: Spatiotemporal Learning of High-dimensional Cell Fate

主讲人:聂青 教授(加州大学尔湾分校)

报告时间:2024年04月12日上午10:00-11:00

讲座地点:深圳大学粤海校区汇星楼一楼一号教室

内容概述:Cells make fate decisions in response to dynamic environments, and multicellular structures emerge from multiscale interplays among cells and genes in space and time. The recent single-cell genomics technology provides an unprecedented opportunity to profile cells for all their genes. While those measurements provide high-dimensional gene expression profiles for all cells, it requires fixing individual cells that lose many important spatiotemporal information. Is it possible to infer temporal relationships among cells from single or multiple snapshots? How to recover spatial interactions among cells, for example, cell-cell communication? In this talk I will present our newly developed computational tools that are mostly based on dynamical models and machine-learning methods, with a focus on inference and analysis of transitional properties of cells and cell-cell communication using both high-dimensional single-cell and spatial transcriptomics, as well as multi-omics data for some cases. Through their applications to various complex systems in development, regeneration, and diseases, we show the discovery power of such methods in addition to identifying areas for further method development for spatiotemporal analysis of single-cell data.

主讲人简介:Dr. Qing Nie is a University of California Presidential Chair and a Distinguished Professor of Mathematics and Developmental & Cell Biology at University of California, Irvine. Dr. Nie is also a University of California Presidential Chair, and the director of the NSF-Simons Center for Multiscale Cell Fate Research jointly funded by NSF and the Simons Foundation – one of the four national centers on mathematics of complex biological systems. In research, he uses systems biology and data-driven methods to study complex biological systems with focuses on single-cell analysis, multiscale modeling, cellular plasticity, stem cells, embryonic development, and their applications to diseases. Dr. Nie has published more than 200 research articles, including several papers in Nature, Nature Methods, and Nature Machine Intelligence. In training, Dr. Nie has supervised more than 60 postdoctoral fellows and PhD students, with many of them working in academic institutions. Dr. Nie is a fellow of the American Association for the Advancement of Science (AAAS), American Physical Society (APS), Society for Industrial and Applied Mathematics (SIAM), and American Mathematical Society (AMS).

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