Kinase-specific phosphorylation plays a critical role in cellular signaling and various diseases. However, even in model organisms, the substrates of most kinases remain unidentified. Currently, there is no reliable method to predict kinase-substrate relationships. In this study, we introduce an innovative approach leveraging an autoregressive model to predict kinase-substrate pairs. Unlike traditional methods focused on predicting site-specific phosphorylation, our approach addresses kinase-specific protein subst…