Machine Learning and Data Integration in Spatial Biology
Chairs: Julio Saez-Rodriguez, Leeat Keren
Thursday, 12.12.2024, 2:00 pm
Leeat Keren
Molecular Cell Biology, Weizmann Institute of science, Rehovot, Israel
Escalating high-dimensional imaging for cancer research
Tumors are spatially organized ecosystems that are comprised of distinct cell types, each of which can assume a variety of phenotypes defined by coexpression of multiple proteins. To underscore this complexity it is essential to interrogate cellular expression patterns within their native context in the tissue. I will describe technological and computational advancements in multiplexed imaging, and demonstrate its application to study the tumor microenvironment.
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Dr. Leeat Keren is an assistant professor in the department of Molecular Cell Biology, Weizmann Institute of science. She completed her Ph.D. in computational biology in the Weizmann Institute of Science in 2016 and her postdoc with Dr. Michael Angelo in Stanford University in 2020. She is an Azrieli Faculty Fellow, a recipient of the Dale F. Frey breakthrough scientist award from the Damon Runyon Cancer Research Foundation and a recipient of the James Heineman Research Award.
Oliver Stegle
Computational Genomics & Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg Germany
BioSketch
Prof. Dr. Oliver Stegle is the Head of the Computational Genomics and Systems Genetics Division at the German Cancer Research Center (DKFZ) and group leader at EMBL in Heidelberg, Germany. His laboratory is developing and applying statistical and machine learning methods for deciphering molecular variation across individuals, space and time. He coordinates the German Human-Genome-Phenome Archive, the health program of the European Laboratory for Learning and Intelligent Systems and is an ERC investigator.
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