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Drug similarity has been studied to support downstream clinical tasks such as inferring novel properties of drugs (e.g.
Ttd: Therapeutic target database
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Clinically important drug interactions with zopiclone, zolpidem and zaleplon
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Machine learning-based prediction of drug-drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
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http://astro.temple.edu/~tua87106/drugreposition.html
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Label propagation prediction of drug-drug interactions based on clinical side effects
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Drug drug interaction through molecular structure similarity analysis
S. Vilar, R. Harpaz, E. Uriarte, L. Santana, R. Rabadan, and C. Friedman
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Predicting potential side effects of drugs by recommender methods and ensemble learning
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Multitask dyadic prediction and its application in prediction of adverse drug-drug interaction
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Modeling Relational Data with Graph Convolutional Networks
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Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data
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