SPARSE GENERALIZED LINEAR MODEL WITH L 0 APPROXIMATION FOR FEATURE SELECTION AND PREDICTION WITH BIG OMICS DATA

Sparse generalized linear model with L 0 approximation for feature selection and prediction with big omics data

Abstract Background Feature selection and prediction are the most important tasks for big data mining.The common strategies for feature selection in big data mining are L Seat Adjustment Lever 1, SCAD and MC+.However, none of the existing algorithms optimizes L 0, which penalizes the number of nonzero features directly.Results In this paper, we dev

read more



New open-source software for subcellular segmentation and analysis of spatiotemporal fluorescence signals using deep learning

Summary: Cellular imaging instrumentation advancements as well as readily available optogenetic and fluorescence sensors have yielded a profound Plate need for fast, accurate, and standardized analysis.Deep-learning architectures have revolutionized the field of biomedical image analysis and have achieved state-of-the-art accuracy.Despite these adv

read more