Event Date: September 20, 2017
Location: 126 Clements Hall
Time: 3:30-4:30 pm
Abstract: The recent advance of single-cell RNAseq technology makes it possible to dissect heterogeneous tumor tissue samples and deconvolute the molecular signal into specific cell types. This technique generates high-dimensional gene expression profile data in a very sparse fashion. In a current study, by unsupervised clustering strategy and mapping the centroid of signal, we successfully identify multiple subpopulations of cell types and characterize their roles in tumor progression.
Link for more information: http://www.smu.edu/Dedman/Academics/Departments/Math/Seminars