Single-cell, Spatial, and Multimodal Analyses for Studying Biological Systems

Abstract: Complex organisms function through many types of interactions. Thanks to advancements of experimental technologies and accumulation of resulting data, it is now possible to characterize individual biological entities and their relationships precisely and holistically. In this seminar, I will describe some of our recent work that utilizes single-cell technologies to study cell-to-cell variability and identify rare signals, spatial technologies to study relationships between cells in the tissue environment, and integration of diverse data types to study how different biological mechanisms work together. I will describe some data analysis and modeling methods we have developed, as well as their applications in the study of cancer, aging, and neurodegenerative diseases.

Bio: Dr. Kevin Yip is Professor and Director of Center for Data Science and Artificial Intelligence at Sanford Burnham Prebys Medical Discovery Institute. Dr. Yip received his PhD in computer science from Yale University. Before joining Sanford Burnham Prebys, he was a faculty in the Department of Computer Science and Engineering at Chinese University of Hong Kong for 10 years. Dr. Yip’s laboratory has three main research directions, including 1) development of computational methods for analyzing data produced by latest experimental technologies, 2) modeling gene regulatory mechanisms using artificial intelligence, and 3) application of the methods in studying human health and diseases.