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Cancer is a heterogeneous disease, with variation across individuals with regard to aspects such as rate of progression, response to treatment, and survival time. Although the polyclonal nature of many cancers and the role of evolutionary processes in tumor progression was first established in the late 1970’s, increased attention has recently been given to these processes as their potential role in clinical outcomes has become more widely recognized. This has in part been motivated by the availability of data at a finer scale than ever before, though technological developments such as single-cell sequencing. Given the availability of such data, there is now a need for models and methods that can produce realistic pictures of the evolutionary history of a tumor. In this workshop, we explore the use of mathematical and statistical models that include an evolutionary component to study cancer at various scales, including evolution that occurs within individual tumors, across transmissible cancers, and within populations, possibly in conjunction with environmental and genetic factors.
A full three days of speakers, workshop and panel sessions!
Amir Asiaee T. - Mathematical Biosciences Institute, The Ohio State University
David Basanta - Moffitt Cancer Center
Kimberly Bussey - Department of Biomedical Informatics, Arizona State University
Jasmine Foo - School of Mathematics, University of Minnesota Twin Cities
Katharina Jahn - Department of Biosystems Science and Engineering, ETH Zürich
Harsh Jain - Department of Mathematics, Florida State University
Mary Kuhner - Genome Sciences Department, University of Washington
Carlo Maley - School of Life Sciences, Arizona State University
Michael Metzger - Metzger Lab, Pacific Northwest Research Institute
Luay Nakhleh - Department of Computer Science, Rice University
Ben Raphael - Computer Science Department, Princeton University
Russell Schwartz - Department ofBiological Sciences, Carnegie Mellon University
Daniel Stover - Department of Internal Medicine, The Ohio State University
Chi Wang - College of Public Health, University of Kentucky
Tianjian Zhou - University of Chicago