Talk Title: Measuring and predicting cancer evolution with genomic data Abstract: We combine theoretical population genetics models of evolving populations with machine learning methods to analyze cancer genomic data, with specific focus on whole-genome sequencing. This allows deconvoluting the signal in the data to measure clonal structures, selective advantage coefficients of subclones, and mutation […]
For seminar recording, please click here Talk Title: Detecting effects of alterations in chromosome structure on cancer cellular fitness Abstract: Structural variants—alterations in chromosome structure—affect far more of the cancer genome than any other type of genetic event. Indeed, large-scale aneuploidies were the first genetic alteration posited to contribute to cancer. Because of their complexity […]
Meeting Recording: https://web.microsoftstream.com/video/c84847fc-b1d2-4ec2-a7c3-5243f063cc3f Talk Title: Learning Interpretable Models on Complex Medical Data Abstract: Machine learning as a field has become more and more important due to the ubiquity of data collection in various disciplines. Coupled with this data collection is the hope that new discoveries or knowledge can be learned. My research spans both fundamental […]