YoVDO

Discrete Morse Graph Skeletonization and Application to Local Structures of scRNA-seq Data

Offered By: Institute for Pure & Applied Mathematics (IPAM) via YouTube

Tags

Topological Data Analysis Courses Data Visualization Courses Computational Biology Courses High-dimensional Data Courses Persistent Homology Courses Discrete Morse Theory Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a 52-minute conference talk on discrete Morse graph skeletonization and its application to analyzing local structures of scRNA-seq data. Delve into the emerging field of topological and geometric data analysis (TGDA) as Yusu Wang from the University of California, San Diego, presents at IPAM's Mathematical Approaches for Connectome Analysis Workshop. Discover how topological objects from discrete Morse theory and persistent homology can be utilized to extract graph skeletons from high-dimensional point cloud data. Learn about the practical application of this graph skeletonization method in studying and quantifying differences in local structures of scRNA-seq datasets across various brain regions. Gain insights into this collaborative research effort with L. Magee, R. Gala, U. Sumbul, and M. Hawrylycz, recorded on February 16, 2024.

Syllabus

Yusu Wang - Discrete Morse Graph Skeletonization & Application to Local Structures of scRNA-seq Data


Taught by

Institute for Pure & Applied Mathematics (IPAM)

Related Courses

Hardness Results in Discrete Morse Theory for 2-Complexes
Applied Algebraic Topology Network via YouTube
Morse-Based Fibering of the Rank Invariant
Applied Algebraic Topology Network via YouTube
Ulrich Bauer: Ripser - Efficient Computation of Vietoris–Rips Persistence Barcodes
Hausdorff Center for Mathematics via YouTube
Morse Theory for Group Presentations and the Persistent Fundamental Group
Applied Algebraic Topology Network via YouTube
Claudia Landi - Multi-parameter Persistence from the Viewpoint of Discrete Morse Theory
Applied Algebraic Topology Network via YouTube