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.