Department of Biostatistics & Medical Informatics Seminar with Daifeng Wang, UW-Madison
AI-Driven Single-Cell Analysis: From Disease Mechanisms to Therapeutic Discovery
Event Details
Date
Friday, September 18, 2026
Time
Noon-1 p.m.
Location
Description
Emerging single-cell genomics provides an unprecedented view of cellular and molecular
heterogeneity across diseases and clinical phenotypes, yet translating these complex data into mechanistic and therapeutic insight remains challenging. This talk presents an AI-driven computational framework for single-cell analysis that integrates multimodal, graph-based, and physics-informed learning to connect genes, cell functions and dynamics, disease phenotypes, and repurposed drugs.
heterogeneity across diseases and clinical phenotypes, yet translating these complex data into mechanistic and therapeutic insight remains challenging. This talk presents an AI-driven computational framework for single-cell analysis that integrates multimodal, graph-based, and physics-informed learning to connect genes, cell functions and dynamics, disease phenotypes, and repurposed drugs.
Cost
Free
Contact
Accessibility
We value inclusion and access for all participants and are pleased to provide reasonable accommodations for this event. Please email juan.caicedo@wisc.edu to make a disability-related accommodation request. Reasonable effort will be made to support your request.