S22-041 Reconfiguration of Tabular Data for Discovery of Deep Interaction Features and its Applications in Analysis of Multidimensional Data Stanford scientists have developed a high-performance informatics framework for deep learning analyses of high dimensional (HD) omics data. Md Tauhidul Islam Lei Xing
S19-470 Hummingbird: Predicting Best Configurations for Genomics Cloud Computing Stanford researchers developed a framework called 'Hummingbird' that predicts the cheapest, fastest and most efficient configurations to execute genomics pipelines on the cloud. Amir Bahmani Vandhana Krishnan Cuiping Pan Ziye Xing Utsab Ray Michael Snyder Philip Tsao