Inference and analysis of cell-differentiation associated signaling using multiple computational methods


Understanding the mechanisms of cellular differentiation requires comprehensive signaling
transduction networks, systems-level analyses of those networks, and information on signal-producing
cells. Here we introduce and compare two computational toolkits that can quantitatively infer and
analyze intercellular signaling networks from scRNA-seq data. (1) CellChat: an R package that can be
applied to predict major signaling inputs and outputs for cells and how those cells and signals coordinate
for functions using network analysis and pattern recognition approaches, which is significant in
understanding global communications between different cell-population groups. (2) ExFinder: an R
package that can be used to identify the differentiation-associated ligands that are produced by
undifferentiating cells (external signals) and quantitatively analyze their corresponding networks. Such
identification is critical for revealing the driving factors of cellular differentiation, inferring gene
regulatory networks, and improving the experimental design.


Math Bio Seminar
Sept. 23, 2022
12 PM - 1 PM, Arizona time
WXLR A309 and virtual via Zoom

Those joining remotely can use the link:


Changhan He
Postdoctoral Fellow
Department of Mathematics
University of California - Irvine

WXLR A309 and virtual via Zoom