ArticleScientific reports2021
A machine learning framework for predicting drug-drug interactions.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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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
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of molecular representation learning foundation models.Briefings in bioinformatics · 2026Pooled it
- Integration of artificial intelligence applications in clinical pharmacy services: A scoping review.Future healthcare journal · 2026Review
- Methods for Detecting Suspicious Information From Individual Transactions of Pharmaceutical Products via Twitter (now X): Retrospective Observational Study.Journal of medical Internet research · 2026Observational
- FSSM-DDI: Fusion State Space Model for predicting drug-drug interaction using social-media and drug descriptions.BMC biology · 2026Article
- Implications of ferritinophagy in cardiovascular diseases and its pharmacological modulation: underlying mechanisms and clinical translation strategies.Cellular & molecular biology letters · 2026Review
- DisenKGE-DDI: A Knowledge Graph Embedding Framework Based on Disentangled Graph Attention Networks for Drug-Drug Interaction Prediction.Interdisciplinary sciences, computational life sciences · 2026Article
- From Knowledge Graphs to Digital Twins: Perspectives on Modeling Patient Outcomes for Health Care Quality Assessment.Journal of medical Internet research · 2026Article
- MFCN-DDI: Capsule network based on multimodal feature for multitype drug-drug interaction prediction.Quantitative biology (Beijing, China) · 2026Article
- Advancing Drug Discovery with AI: Machine and Deep Learning Strategies for Target Identification and Precision Nanomedicine.International journal of nanomedicine · 2026Review
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- A comprehensive landscape of AI applications in broad-spectrum drug interaction prediction: a systematic review.Journal of cheminformatics · 2025Review
- Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2025Article
- Human intestinal enteroids: Nonclinical applications for predicting oral drug disposition, toxicity, and efficacy.Pharmacology & therapeutics · 2025Review
- SCATrans: semantic cross-attention transformer for drug-drug interaction predication through multimodal biomedical data.BMC bioinformatics · 2025Article
- A Review on New Frontiers in Drug-Drug Interaction Predictions and Safety Evaluations with In Vitro Cellular Models.Pharmaceutics · 2025Review
- Borylated 5-Membered Ring Iminosugars: Detailed Nuclear Magnetic Resonance Spectroscopic Characterisation, and Method for Analysis of Anomeric and Boron Equilibria.Molecules (Basel, Switzerland) · 2025Article
- A novel deep sequential learning architecture for drug drug interaction prediction using DDINet.Scientific reports · 2025Article
- Artificial Intelligence Models and Tools for the Assessment of Drug-Herb Interactions.Pharmaceuticals (Basel, Switzerland) · 2025Review
- PSO-FeatureFusion: a general framework for fusing heterogeneous features via particle swarm optimization.Bioinformatics advances · 2025Article
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Authors and funding
2 authors.
Funding
Abstract
Understanding drug-drug interactions is an essential step to reduce the risk of adverse drug events before clinical drug co-prescription. Existing methods, commonly integrating heterogeneous data to increase model performance, often suffer from a high model complexity, As such, how to elucidate the molecular mechanisms underlying drug-drug interactions while preserving rational biological interpretability is a challenging task in computational modeling for drug discovery. In this study, we attempt to investigate drug-drug interactions via the associations between genes that two drugs target. For this purpose, we propose a simple f drug target profile representation to depict drugs and drug pairs, from which an l
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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.