学术报告(周沛劼 2024.3.1)

The dynamical system analysis of single-cell omics data

发布人:姚璐 发布日期:2024-02-22
主题
The dynamical system analysis of single-cell omics data
活动时间
-
活动地址
新数学楼415
主讲人
周沛劼 研究员(北京大学前沿交叉学科研究院国际机器学习中心)
主持人
孙小强

摘要:Single-cell sequencing technologies provide unprecedented resolution for studying the dynamic process of cell-state transitions during development and complex disease. In this talk, I will discuss how machine learning has enabled us to overcome this challenge and use dynamical systems techniques to analyze scRNA-seq data. I will introduce the low-dimensional dynamical manifold to identify attractor basins and transition probabilities in snapshot data. I will also present the usage of non-equilibrium dynamical systems theory to analyze attractor stability and identify transition-driving genes in gene expression and splicing processes. Finally, I will discuss our efforts to construct a time-varying landscape, which interpolates non-stationary time-series scRNA-seq data using Wasserstein-Fisher-Rao metric, unbalanced optimal transport and its neural network-based partial differential equation implementations.