The NIAID Data Science Seminar is brought to you by the Office of Data Science and Emerging Technologies (ODSET). This is held on the first Friday of each month at 12:00 noon ET. Seminar topics include informatics/data science research in immune-mediated and infectious disease conducted, funded, or relevant to NIAID’s mission. This also provide a forum for disseminating related research and an opportunity for discussions and collaborations.
Machine Learning for Modeling Dynamics of Immune Cell States
Date: Friday, 12/3/2021 at 12 pm ET
Elham Azizi, Ph.D.
Herbert & Florence Irving Assistant Professor of Cancer Data Research at the Irving Institute for Cancer Dynamics
Assistant Professor of Biomedical Engineering
Recent genomic and imaging technologies that measure features at the resolution of single cells present exciting opportunities to characterize diverse immune cell states in various disease contexts and elucidate their circuitry and role in driving response to therapies. However, analyzing and integrating single-cell data across patients, time points, and data modalities involves significant statistical and computational challenges. Dr. Azizi will present a set of machine learning methods developed to address problems such as handling sparsity and noise, distinguishing technical variation from biological heterogeneity, inferring underlying circuitry, and inferring temporal dynamics of immune states in clinical cohorts. Dr. Azizi will also present novel biological insights obtained from applying these methods to cancer systems. These results include continuous phenotypic expansion of immune cells when interfacing with breast tumors and detecting key exhausted T cell subsets with divergent temporal dynamics that define response to immunotherapy in leukemia.
Nomination for topics and other questions or comments can be submitted by email to Steve Tsang