报告人：聂青 教授（加州大学尔湾分校）

报告时间：2024年11月13日9:00—11:00

报告题目：Systems Learning of Single Cells 

地点：雁山校区理四501

报告摘要：Cells make fate decisions in response to dynamic environments, and multicellular structures emerge from multiscale interplays among cells and genes in space and time. While single-cell omics data provides an unprecedented opportunity to profile cellular heterogeneity, the technology requires fixing the cells, often leading to a loss of spatiotemporal and cell interaction information. How to reconstruct temporal dynamics from single or multiple snapshots of single-cell omics data? How to recover interactions among cells, for example, cell-cell communication from single-cell gene expression data? I will present a suite of our recently developed computational methods that learn the single-cell omics data as a spatiotemporal and interactive system. Those methods are built on a strong interplay among systems biology modeling, dynamical systems approaches, machine-learning methods, and optimal transport techniques. The tools are applied to various complex biological systems in development, regeneration, and diseases to show their discovery power. Finally, I will discuss the methodology challenges in systems learning of single-cell data.

报告人简介：聂青教授是加州大学尔湾分校的数学、发育和细胞生物学杰出教授，同时也是加州大学主席教授（University of California Presidential Chair），同时担任由美国国家科学基金会和西蒙斯基金会联合资助（NSF-Simons）的多尺度细胞命运研究中心主任。聂青教授运用系统生物学和数据驱动方法研究复杂生物系统的定量规律，重点围绕单细胞分析、多尺度建模、细胞可塑性、干细胞、胚胎发育及其在疾病发生机制，取得了一系列具有国际影响力的研究成果。发表了230多篇研究论文，其中近50篇发表在Nature, Nature Methods, Nature Machine Intelligence, Cancer Cell, Developmental Cell, Nature Genetics, PNAS等高影响力学术期刊上。在学生培养方面，他指导了60多名博士后和博士研究生，其中许多人在学术机构担任教职：美国科学促进会（AAAS）会士、美国物理学会（APS）会士、工业和应用数学学会（SIAM）会士以及美国数学学会（AMS）会士。