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Spleen tyrosine kinase (Syk) provides an interesting target for the therapy of Rheumatoid arthritis.Interruption of Syk signaling with an inhibitor may potentially produce an effect on disease activity.In this work,we explored four machine learning (ML) methods,support vector machine (SVM),k-nearest neighbor (k-NN),back-propagation neural network (BPNN) and C4.5 decision tree (C4.5 DT) for predicting Syk inhibitors.