Results 81 to 90 of about 1,936,479 (187)

An integrated dataset for in silico drug discovery

Journal of Integrative Bioinformatics, 2010
Drug development is expensive and prone to failure. It is potentially much less risky and expensive to reuse a drug developed for one condition for treating a second disease, than it is to develop an entirely new compound.
Cockell Simon J, Weile Jochen, Lord Phillip, Wipat Claire, Andriychenko Dmytro, Pocock Matthew, Wilkinson Darren, Young Malcolm, Wipat Anil   +8 more
doaj   +1 more source

Research on drug repositioning based on generative AI

大数据
In view of the problem of fixed drug indication prediction quantity and inability to fully reveal potential indication of drug in current drug repositioning research, this article proposes a generative AI drug repositioning model GenDrugShifter, which ...
GONG Houwu, JIN Min
doaj   +2 more sources

In silico drug repositioning: from large-scale transcriptome data to therapeutics

, 2021
Drug repositioning is an attractive alternative to conventional drug development when new beneficial effects of old drugs are clinically validated because pharmacokinetic and safety profiles are generally already available.
김완규, 이해승
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Exploiting drug-disease relationships for computational drug repositioning

, 2011
Finding new uses for existing drugs, or drug repositioning, has been used as a strategy for decades to get drugs to more patients. As the ability to measure molecules in high-throughput ways has improved over the past decade, it is logical that such data
Atul J. Butte, A. J. Butte, T. Deshpande, Tarangini Deshp, Joel T. Dudley, J. T. Dudley   +5 more
core   +1 more source

Prediction of drug–disease associations based on reinforcement symmetric metric learning and graph convolution network

Frontiers in Pharmacology
Accurately identifying novel indications for drugs is crucial in drug research and discovery. Traditional drug discovery is costly and time-consuming.
Huimin Luo, Huimin Luo, Chunli Zhu, Chunli Zhu, Jianlin Wang, Jianlin Wang, Ge Zhang, Ge Zhang, Junwei Luo, Chaokun Yan, Chaokun Yan, Chaokun Yan   +11 more
doaj   +1 more source

Learning interpretable disease self-representations for drug repositioning [PDF]

, 2019
Drug repositioning is an attractive cost-efficient strategy for the development of treatments for human diseases. Here, we propose an interpretable model that learns disease self-representations for drug repositioning.
Paccanaro, Alberto, Veselkov, Kirill, Frasca, Fabrizio, Bronstein, Michael M, Galeano, Diego, Gonzalez, Guadalupe, Laponogov, Ivan   +6 more
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In silico methods for drug repositioning and drug-drug interaction prediction [PDF]

, 2018
© 2018 Dr. Pathima Nusrath HameedDrug repositioning and drug-drug interaction (DDI) prediction are two fundamental applications having a large impact on drug development and clinical care.
Hameed, Pathima Nusrath
core   +1 more source

The Balanced Matrix Factorization for Computational Drug Repositioning

, 2023
Computational drug repositioning aims to discover new uses of drugs that have been marketed. However, the existing models suffer from the following limitations. Firstly, in the real world, only a minority of diseases have definite treatment drugs.
Chu, Jian, Yang, Genke, Yang, Xinxing
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The processes of reform in Victoria’s alcohol and other drug sector, 2011-2014 [PDF]

, 2014
This paper explores issues and concerns related to the 2014 alcohol and other drug sector recommissioning process in Victoria. Overview In mid-2014, the Victorian Alcohol and Drug Association approached the Drug Policy Modelling Program, at the ...
Drug Policy Modelling Program
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Systems approaches to drug repositioning [PDF]

, 2017
PhD ThesisDrug discovery has overall become less fruitful and more costly, despite vastly increased biomedical knowledge and evolving approaches to Research and Development (R&D).
Mullen, Joseph Michael
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