ArticleChemical science2020
Target identification among known drugs by deep learning from heterogeneous networks.
Article in Chemical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 131 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
131 citing papers in PubMed, 1 synthesis or guideline pooled it, 343 citations in OpenAlex.
- A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation.International journal of molecular sciences · 2023Pooled it
- IMF-DDI: Information Mapping and Fusion Framework for Drug-drug Interaction Prediction.Interdisciplinary sciences, computational life sciences · 2026Article
- A unified framework combining linear and 3D molecular features for robust drug-protein interaction prediction.Cell reports methods · 2026Article
- [Drug repositioning prediction based on dynamic feature learning on heterogeneous graphs].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery.Advanced drug delivery reviews · 2026Review
- Artificial Intelligence to Guide Repurposing of Drugs.Annual review of medicine · 2026Review
- AΙ-Driven Drug Repurposing: Applications and Challenges.Medicines (Basel, Switzerland) · 2025Review
- Advancing active compound discovery for novel drug targets: insights from AI-driven approaches.Acta pharmacologica Sinica · 2025Review
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- Allostery in Disease: Anticancer Drugs, Pockets, and the Tumor Heterogeneity Challenge.Journal of molecular biology · 2025Review
- Progress of AI-Driven Drug-Target Interaction Prediction and Lead Optimization.International journal of molecular sciences · 2025Review
- DHGT-DTI: Advancing drug-target interaction prediction through a dual-view heterogeneous network with GraphSAGE and Graph Transformer.Journal of pharmaceutical analysis · 2025Article
- Biomolecular Interaction Prediction: The Era of AI.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- MIF-DTI: a multimodal information fusion method for drug-target interaction prediction.Briefings in bioinformatics · 2025Article
- MGPT: A Multi-task Graph Prompt Learning Framework for Drug Discovery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learning.Scientific reports · 2025Article
- Accurate prediction of drug-protein interactions by maintaining the original topological relationships among embeddings.BMC biology · 2025Article
- Drug-target interaction prediction based on graph convolutional autoencoder with dynamic weighting residual GCN.BMC bioinformatics · 2025Article
- Tumors and their microenvironments: Learning from pediatric brain pathologies.Biochimica et biophysica acta. Reviews on cancer · 2025Review
- MixingDTA: improved drug-target affinity prediction by extending mixup with guilt-by-association.Bioinformatics (Oxford, England) · 2025Article
71 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 9 institutions in 4 countries.
Funding
Abstract
Without foreknowledge of the complete drug target information, development of promising and affordable approaches for effective treatment of human diseases is challenging. Here, we develop deepDTnet, a deep learning methodology for new target identification and drug repurposing in a heterogeneous drug-gene-disease network embedding 15 types of chemical, genomic, phenotypic, and cellular network profiles. Trained on 732 U.S. Food and Drug Administration-approved small molecule drugs, deepDTnet shows high accuracy (the area under the receiver operating characteristic curve = 0.963) in identifying novel molecular targets for known drugs, outperforming previously published state-of-the-art methodologies. We then experimentally validate that deepDTnet-predicted topotecan (an approved topoisomerase inhibitor) is a new, direct inhibitor (IC
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.