ArticleFrontiers in bioengineering and biotechnology2020
Prediction of Drug-Target Interactions From Multi-Molecular Network Based on Deep Walk Embedding Model.
Article in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Anomaly Detection with Graph Embedding in Bioinformatics: A Survey.Current genomics · 2025Review
- Simplicity within biological complexity.Bioinformatics advances · 2025Article
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- Role of Artificial Intelligence in Drug Discovery and Target Identification in Cancer.Current drug delivery · 2024Review
- Artificial intelligence and machine learning applications for cultured meat.Frontiers in artificial intelligence · 2024Review
- Multimodal multi-task deep neural network framework for kinase-target prediction.Molecular diversity · 2023Article
- GraphCPIs: A novel graph-based computational model for potential compound-protein interactions.Molecular therapy. Nucleic acids · 2023Article
- A lncRNA-disease association prediction tool development based on bridge heterogeneous information network via graph representation learning for family medicine and primary care.Frontiers in genetics · 2023Article
- Article
- The curse and blessing of abundance-the evolution of drug interaction databases and their impact on drug network analysis.GigaScience · 2022Article
- Graph representation learning in biomedicine and healthcare.Nature biomedical engineering · 2022Review
- Multitype drug interaction prediction based on the deep fusion of drug features and topological relationships.PloS one · 2022Article
- Graph neural networks for materials science and chemistry.Communications materials · 2022Review
- A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning.Cancers · 2021Article
- DF-MDA: An effective diffusion-based computational model for predicting miRNA-disease association.Molecular therapy : the journal of the American Society of Gene Therapy · 2021Article
- MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning.Frontiers in genetics · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting drug-target interactions (DTIs) is crucial in innovative drug discovery, drug repositioning and other fields. However, there are many shortcomings for predicting DTIs using traditional biological experimental methods, such as the high-cost, time-consumption, low efficiency, and so on, which make these methods difficult to widely apply. As a supplement, the
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