Temporal Modeling Using Single-Cell Transcriptomics

About this Class

Dr. Ziv Bar-Joseph FORE Systems Biology Professor of Computer Science Machine Learning Department Computational Biology Department School of Computer Science Carnegie Mellon University

Biological processes, including those involved in immune response, disease progression and development, are often dynamic. To fully understand and model regulatory networks that are activated as part of these processes requires the integration of static and times series bulk and single cell data. I will discuss methods for designing experiments for studying such systems and machine learning methods for the analysis and integration of profiled data to reconstruct networks for within and between interacting cells and cell types. An application of these methods for improving protocols for the differentiation of iPSCs to lung cells and liver organoids will be presented.