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Biases of Drug–Target Interaction Network Data [PDF]
, 2014 Network based prediction of interaction between drug compounds and target proteins is a core step in the drug discovery process. The availability of drugtarget interaction data has boosted the development of machine learning methods for the in silico prediction of drugtarget interactions.
Laarhoven, T. van, Marchiori, E.
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Drug-target interaction prediction using semi-bipartite graph model and deep learning
BMC Bioinformatics, 2020 Background Identifying drug-target interaction is a key element in drug discovery. In silico prediction of drug-target interaction can speed up the process of identifying unknown interactions between drugs and target proteins.
Hafez Eslami Manoochehri +1 more
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Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile. [PDF]
PLoS ONE, 2013 In silico discovery of interactions between drug compounds and target proteins is of core importance for improving the efficiency of the laborious and costly experimental determination of drug-target interaction.
Twan van Laarhoven, Elena Marchiori
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BMC Bioinformatics, 2021 Background Wet-lab experiments for identification of interactions between drugs and target proteins are time-consuming, costly and labor-intensive. The use of computational prediction of drug–target interactions (DTIs), which is one of the significant ...
Ali Ghanbari Sorkhi +3 more
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A semi-supervised method for drug-target interaction prediction with consistency in networks. [PDF]
PLoS ONE, 2013 Computational prediction of interactions between drugs and their target proteins is of great importance for drug discovery and design. The difficulties of developing computational methods for the prediction of such potential interactions lie in the ...
Hailin Chen, Zuping Zhang
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A Novel Deep Neural Network Technique for Drug–Target Interaction
Pharmaceutics, 2022 Drug discovery (DD) is a time-consuming and expensive process. Thus, the industry employs strategies such as drug repositioning and drug repurposing, which allows the application of already approved drugs to treat a different disease, as occurred in the ...
Jackson G. de Souza +2 more
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Gaussian interaction profile kernels for predicting drug–target interaction [PDF]
Bioinformatics, 2011 Abstract Motivation: The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of all drug–target pairs in current datasets are experimentally validated interactions.
Laarhoven, T.M. van +2 more
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BMC Bioinformatics, 2022 Predicting drug–target interactions (DTIs) has become an important bioinformatics issue because it is one of the critical and preliminary stages of drug repositioning.
Reza Hassanzadeh +1 more
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Challenges and solutions in drug-target interaction prediction [PDF]
, 2020 When a drug is developed, it is designed so that it interacts with a specific target of interest in order to achieve the desired therapeutic effect. However, it is quite common to later find that the developed drug also interacts with multiple other targets that were not intended during its development.
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Computational Discovery of Putative Leads for Drug Repositioning through Drug-Target Interaction Prediction. [PDF]
PLoS Computational Biology, 2016 De novo experimental drug discovery is an expensive and time-consuming task. It requires the identification of drug-target interactions (DTIs) towards targets of biological interest, either to inhibit or enhance a specific molecular function.
Edgar D Coelho +2 more
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