Improving the Prediction of Potential Kinase Inhibitors with Feature Learning on Multisource Knowledge

ConclusionIn conclusion, our computational framework of FLMTS for improving the prediction of potential kinase inhibitors successfully aggregates feature information from multisource knowledge, yielding better prediction performance than existing state-of-the-art methods.Graphical Abstract

Source: Interdisciplinary Sciences, Computational Life Sciences - May 10, 2022 Category: Bioinformatics Source Type: research