Appears in collection : 2019 - T1 - WS3 - Imaging and machine learning

Many problems in genomics require the ability to identify relevant features in data sets containing many more orders of magnitude than samples. This setup poses different statistical and computational challenges, and traditional feature selection methods fall short. In my talk, I will present several ways to incorporate prior knowledge of the structure of the features to address this problem.