Results 21 to 30 of about 888,632 (296)

UnbiasedDTI: Mitigating Real-World Bias of Drug-Target Interaction Prediction by Using Deep Ensemble-Balanced Learning

open access: yesMolecules, 2022
Drug-target interaction (DTI) prediction through in vitro methods is expensive and time-consuming. On the other hand, computational methods can save time and money while enhancing drug discovery efficiency.
Aida Tayebi   +6 more
doaj   +1 more source

A Federated Learning Benchmark for Drug-Target Interaction

open access: yesCompanion Proceedings of the ACM Web Conference 2023, 2023
This paper is the accepted version of ACM copyrighted material published at the WWW'23 ...
Gianluca Mittone   +4 more
openaire   +2 more sources

DeepDrug: A general graph‐based deep learning framework for drug‐drug interactions and drug‐target interactions prediction

open access: yesQuantitative Biology, 2023
Computational methods for DDIs and DTIs prediction are essential for accelerating the drug discovery process. We proposed a novel deep learning method DeepDrug, to tackle these two problems within a unified framework.
Qijin Yin   +5 more
doaj   +1 more source

Identification of drug-target interaction by a random walk with restart method on an interactome network

open access: yesBMC Bioinformatics, 2018
Background Identification of drug-target interactions acts as a key role in drug discovery. However, identifying drug-target interactions via in-vitro, in-vivo experiments are very laborious, time-consuming.
Ingoo Lee, Hojung Nam
doaj   +1 more source

Biases of Drug–Target Interaction Network Data [PDF]

open access: yes, 2014
Network based prediction of interaction between drug compounds and target proteins is a core step in the drug discovery process. The availability of drug—target interaction data has boosted the development of machine learning methods for the in silico prediction of drug—target interactions.
Laarhoven, T. van, Marchiori, E.
openaire   +2 more sources

Drug-target interaction prediction using semi-bipartite graph model and deep learning

open access: yesBMC 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
doaj   +1 more source

Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile. [PDF]

open access: yesPLoS 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
doaj   +1 more source

Drug-drug interactions in the hospital [PDF]

open access: yes, 2007
Introduction Drug interaction screening programs are an important tool to check prescriptions of multiple drugs for potential drug-drug interactions (pDDIs). Several programs are available on the market.
Vonbach, Priska
core   +1 more source

Drug–target interaction prediction using unifying of graph regularized nuclear norm with bilinear factorization

open access: yesBMC 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
doaj   +1 more source

Drug-Disease Severity and Target-Disease Severity Interaction Networks in COVID-19 Patients [PDF]

open access: yes, 2022
Drug interactions with other drugs are a well-known phenomenon. Similarly, however, pre-existing drug therapy can alter the course of diseases for which it has not been prescribed.
Verena Schöning   +3 more
core   +1 more source

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