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In this paper, we developed a semi-supervised neural network-based strategy called EXP2SL to accurately recognize SL interactions through the L1000 gene expression profiles. Through a systematic assessment regarding the SL datasets of three different cell outlines, we demonstrated that our model achieved much better performance as compared to standard methods and verified the potency of utilising the L1000 gene appearance features together with semi-supervise education technique i