Results 11 to 20 of about 709,328 (257)
A novel method for drug-target interaction prediction based on graph transformers model
BMC Bioinformatics, 2022 Background Drug-target interactions (DTIs) prediction becomes more and more important for accelerating drug research and drug repositioning. Drug-target interaction network is a typical model for DTIs prediction.
Hongmei Wang +4 more
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Mapping drug-target interaction networks [PDF]
2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009 Molecular polypharmacological studies have gained more and more attention as they are important in predicting drug off-target properties and potential toxicity/side effect. The explosive growth of biomedical data provides us an opportunity to develop novel strategies to conduct such studies by analyzing molecular interaction networks. In this paper, we
Longzhang Tian,, Shuxing Zhang,
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The RAS–Effector Interaction as a Drug Target [PDF]
Cancer Research, 2017 Abstract About a third of all human cancers harbor mutations in one of the K-, N-, or HRAS genes that encode an abnormal RAS protein locked in a constitutively activated state to drive malignant transformation and tumor growth. Despite more than three decades of intensive research aimed at the discovery of RAS-directed therapeutics ...
Adam B, Keeton +2 more
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Drug–target interaction prediction via multiple classification strategies
BMC Bioinformatics, 2022 Background Computational prediction of the interaction between drugs and protein targets is very important for the new drug discovery, as the experimental determination of drug-target interaction (DTI) is expensive and time-consuming.
Qing Ye, Xiaolong Zhang, Xiaoli Lin
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Big Data and Cognitive Computing, 2021 Coronavirus disease 2019 pandemic spreads rapidly and requires an acceleration in the process of drug discovery. Drug repurposing can help accelerate the drug discovery process by identifying new efficacy for approved drugs, and it is considered an ...
Aulia Fadli +4 more
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Molecules, 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
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Quantitative 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
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A Federated Learning Benchmark for Drug-Target Interaction
Companion 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
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Application of Machine Learning for Drug–Target Interaction Prediction
Frontiers in Genetics, 2021 Exploring drug–target interactions by biomedical experiments requires a lot of human, financial, and material resources. To save time and cost to meet the needs of the present generation, machine learning methods have been introduced into the prediction ...
Lei Xu, Xiaoqing Ru, Rong Song
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BMC 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
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