Deep learning identifies explainable reasoning paths of mechanism of action for drug repurposing from multilayer biological network
The discovery and repurposing of drugs require a deep understanding of the mechanism of
drug action (MODA). Existing computational methods mainly model MODA with the protein …
drug action (MODA). Existing computational methods mainly model MODA with the protein …
A machine learning and network framework to discover new indications for small molecules
Drug repurposing, identifying novel indications for drugs, bypasses common drug
development pitfalls to ultimately deliver therapies to patients faster. However, most …
development pitfalls to ultimately deliver therapies to patients faster. However, most …
Toward heterogeneous information fusion: bipartite graph convolutional networks for in silico drug repurposing
Motivation Mining drug–disease association and related interactions are essential for
developing in silico drug repurposing (DR) methods and understanding underlying …
developing in silico drug repurposing (DR) methods and understanding underlying …
KGML-xDTD: a knowledge graph–based machine learning framework for drug treatment prediction and mechanism description
Background Computational drug repurposing is a cost-and time-efficient approach that aims
to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It …
to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It …
Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data
Deep learning is rapidly advancing many areas of science and technology with multiple
success stories in image, text, voice and video recognition, robotics, and autonomous …
success stories in image, text, voice and video recognition, robotics, and autonomous …
GCMM: graph convolution network based on multimodal attention mechanism for drug repurposing
F Zhang, W Hu, Y Liu - BMC bioinformatics, 2022 - Springer
Background The main focus of in silico drug repurposing, which is a promising area for
using artificial intelligence in drug discovery, is the prediction of drug–disease relationships …
using artificial intelligence in drug discovery, is the prediction of drug–disease relationships …
deepDR: a network-based deep learning approach to in silico drug repositioning
Motivation Traditional drug discovery and development are often time-consuming and high
risk. Repurposing/repositioning of approved drugs offers a relatively low-cost and high …
risk. Repurposing/repositioning of approved drugs offers a relatively low-cost and high …
[HTML][HTML] AI-DrugNet: A network-based deep learning model for drug repurposing and combination therapy in neurological disorders
Discovering effective therapies is difficult for neurological and developmental disorders in
that disease progression is often associated with a complex and interactive mechanism …
that disease progression is often associated with a complex and interactive mechanism …
A novel computational approach for drug repurposing using systems biology
Motivation Identification of novel therapeutic effects for existing US Food and Drug
Administration (FDA)-approved drugs, drug repurposing, is an approach aimed to …
Administration (FDA)-approved drugs, drug repurposing, is an approach aimed to …
Breaking the paradigm: Dr Insight empowers signature-free, enhanced drug repurposing
Motivation Transcriptome-based computational drug repurposing has attracted considerable
interest by bringing about faster and more cost-effective drug discovery. Nevertheless, key …
interest by bringing about faster and more cost-effective drug discovery. Nevertheless, key …
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