AIMC Topic: Drug Repositioning

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Deep learning prediction of chemical-induced dose-dependent and context-specific multiplex phenotype responses and its application to personalized alzheimer's disease drug repurposing.

PLoS computational biology Aug 11, 2022
Predictive modeling of drug-induced gene expressions is a powerful tool for phenotype-based compound screening and drug repurposing. State-of-the-art machine learning methods use a small number of fixed cell lines as a surrogate for predicting actual...
Humans Algorithms Phenotype Deep Learning Drug Repositioning Alzheimer Disease
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Does adding the drug-drug similarity to drug-target interaction prediction methods make a noticeable improvement in their efficiency?

BMC bioinformatics Jul 14, 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. Therefore, scientists are trying to develop more accurate computational methods fo...
Machine Learning Algorithms Computational Biology Drug Repositioning Drug Interactions
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Learning Multi-Scale Heterogeneous Representations and Global Topology for Drug-Target Interaction Prediction.

IEEE journal of biomedical and health informatics Apr 14, 2022
Identification of interactions between drugs and target proteins plays a critical role not only in drug discovery but also in drug repositioning. Deep integration of inter-connections and intra-similarities between heterogeneous multi-source data abo...
Humans Neural Networks, Computer Algorithms Drug Development Proteins Drug Repositioning
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GEFA: Early Fusion Approach in Drug-Target Affinity Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Apr 1, 2022
Predicting the interaction between a compound and a target is crucial for rapid drug repurposing. Deep learning has been successfully applied in drug-target affinity (DTA)problem. However, previous deep learning-based methods ignore modeling the dire...
Neural Networks, Computer Drug Development Proteins Drug Repositioning Amino Acid Sequence
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Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.

Aging Mar 29, 2022
Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to cla...
Artificial Intelligence Drug Discovery Proteins Drug Repositioning
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Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning.

Scientific reports Mar 19, 2022
Drug-target interaction (DTI) prediction plays a crucial role in drug repositioning and virtual drug screening. Most DTI prediction methods cast the problem as a binary classification task to predict if interactions exist or as a regression task to p...
Machine Learning Drug Development Drug Repositioning
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What are the current challenges for machine learning in drug discovery and repurposing?

Expert opinion on drug discovery Mar 8, 2022
Humans Machine Learning Drug Discovery Drug Repositioning
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DeepFusion: A deep learning based multi-scale feature fusion method for predicting drug-target interactions.

Methods (San Diego, Calif.) Feb 24, 2022
Predicting drug-target interactions (DTIs) is essential for both drug discovery and drug repositioning. Recently, deep learning methods have achieved relatively significant performance in predicting DTIs. Generally, it needs a large amount of approve...
Neural Networks, Computer Drug Discovery Deep Learning Proteins Drug Repositioning
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Defining clinical outcome pathways.

Drug discovery today Feb 16, 2022
Here, we propose a broad concept of 'Clinical Outcome Pathways' (COPs), which are defined as a series of key molecular and cellular events that underlie therapeutic effects of drug molecules. We formalize COPs as a chain of the following events: mole...
Drug Discovery Drug Repositioning Knowledge Bases Knowledge
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Graph Convolutional Autoencoder and Generative Adversarial Network-Based Method for Predicting Drug-Target Interactions.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2022
The computational prediction of novel drug-target interactions (DTIs) may effectively speed up the process of drug repositioning and reduce its costs. Most previous methods integrated multiple kinds of connections about drugs and targets by construct...
Neural Networks, Computer Drug Repositioning Pharmaceutical Preparations Drug Interactions
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