Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic

Abstract

Drug-target interaction studies are important because they can predict drugs' unexpected therapeutic or adverse side effects. In silico predictions of potential interactions are valuable and can focus effort on in vitro experiments. We propose a prediction framework that represents the problem using a bipartite graph of drug-target interactions augmented… (More)
DOI: 10.1109/TCBB.2014.2325031

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