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Journal Articles IEEE Journal of Biomedical and Health Informatics Year : 2023

Graph Regularized Probabilistic Matrix Factorization for Drug-Drug Interactions Prediction

Abstract

Co-administration of two or more drugs simultaneously can result in adverse drug reactions. Identifying drug-drug interactions (DDIs) is necessary, especially for drug development and for repurposing old drugs. DDI prediction can be viewed as a matrix completion task, for which matrix factorization (MF) appears as a suitable solution. This paper presents a novel Graph Regularized Probabilistic Matrix Factorization (GRPMF) method, which incorporates expert knowledge through a novel graph-based regularization strategy within an MF framework. An efficient and sounded optimization algorithm is proposed to solve the resulting non-convex problem in an alternating fashion. The performance of the proposed method is evaluated through the DrugBank dataset, and comparisons are provided against state-of-the-art techniques. The results demonstrate the superior performance of GRPMF when compared to its counterparts.
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Dates and versions

hal-04089977 , version 1 (05-05-2023)

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Stuti Jain, Emilie Chouzenoux, Kriti Kumar, Angshul Majumdar. Graph Regularized Probabilistic Matrix Factorization for Drug-Drug Interactions Prediction. IEEE Journal of Biomedical and Health Informatics, 2023, 27 (5), pp.2565-2574. ⟨10.1109/JBHI.2023.3246225⟩. ⟨hal-04089977⟩
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