Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Co...
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of death globally, and research into NSCLC has been accumulating steadily over several years. Drug repositioning is the current trend in the pharmaceutical industry for ident...
Network inference and local classification models have been shown to be useful in predicting newly potential drug-target interactions (DTIs) for assisting in drug discovery or drug repositioning. The idea is to represent drugs, targets, and their int...
BACKGROUND: Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for both drug target discovery and drug repositioning. However, a comprehensive drug-SE association knowledge base does not exi...
The amount of biomedical literature has been increasing rapidly during the last decade. Text mining techniques can harness this large-scale data, shed light onto complex drug mechanisms, and extract relation information that can support computational...
Drug repurposing is an authentic, emerging, and growing aspect of drug development when the demand for new therapeutic solutions is high. Many repurposed drugs have been discovered by serendipity or a non-ordered process driven by chance and sharp ob...
Tumor cell survival depends on the presence of oxygen and nutrients provided by existing blood vessels, particularly when cancer is in its early stage. Along with tumor growth in the vicinity of blood vessels, malignant cells require more nutrients; ...
International journal of pharmaceutics
Jul 25, 2025
Integrating artificial intelligence (AI) into drug discovery has revolutionized pharmaceutical innovation, addressing the challenges of traditional methods that are costly, time-consuming, and suffer from high failure rates. By utilizing machine lear...
Drug repositioning, pivotal in current pharmaceutical development, aims to find new uses for existing drugs, offering an efficient and cost-effective path to drug discovery. In recent years, graph neural network-based deep learning methods have achie...
Journal of chemical information and modeling
Jun 9, 2025
Drug repositioning, which identifies novel therapeutic applications for existing drugs, offers a cost-effective alternative to traditional drug development. However, effectively capturing the complex relationships between drugs and diseases remains c...
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