Research graph
References from Robust prediction of drug combination side effects in realistic settings. Local targets link to admitted publications; unresolved targets remain external evidence.
Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions
10.1038/nbt.3834 · 2017 · External reference
A community computational challenge to predict the activity of pairs of compounds
10.1038/nbt.3052 · 2014 · External reference
DDInter: An online drug-drug interaction database towards improving clinical decision-making and patient safety
10.1093/nar/gkab880 · 2022 · External reference
Changes in prescription and over-the-counter medication and dietary supplement use among older adults in the United States, 2005 vs 2011
10.1001/jamainternmed.2015.8581 · 2016 · External reference
Modeling polypharmacy side effects with graph convolutional networks
10.1093/bioinformatics/bty294 · 2018 · External reference
Predicting drug–target interaction using positive-unlabeled learning
10.1016/j.neucom.2016.03.080 · 2016 · External reference
SSLDTI: A novel method for drug-target interaction prediction based on self-supervised learning
10.1016/j.artmed.2024.102778 · 2024 · External reference
The large language models on biomedical data analysis: A survey
10.1109/jbhi.2025.3530794 · 2025 · External reference
Data-driven prediction of drug effects and interactions
10.1126/scitranslmed.3003377 · 2012 · External reference
DrugBank 3.0: A comprehensive resource for “omics” research on drugs
10.1093/nar/gkq1126 · 2011 · External reference
Drug-drug interaction through molecular structure similarity analysis
10.1136/amiajnl-2012-000935 · 2012 · External reference
Label propagation prediction of drug-drug interactions based on clinical side effects
10.1038/srep12339 · 2015 · External reference
Predicting combinative drug pairs towards realistic screening via integrating heterogeneous features
10.1186/s12859-017-1818-2 · 2017 · External reference
Predicting potential drug-drug interactions on topological and semantic similarity features using statistical learning
10.1371/journal.pone.0196865 · 2018 · External reference
Predicting polypharmacy side-effects using knowledge graph embeddings
2020 · External reference
Prediction of drug-drug interaction events using graph neural networks based feature extraction
10.1038/s41598-022-19999-4 · 2022 · External reference
DeepWalk: online learning of social representations.
10.1145/2623330.2623732 · 2014 · External reference
10.1145/2939672.2939785
10.1145/2939672.2939785 · External reference
Deep learning improves prediction of drug-drug and drug-food interactions
2018 · External reference
Drug-drug interaction prediction with learnable size-adaptive molecular substructures
10.1093/bib/bbab441 · 2022 · External reference
SSI-DDI: Substructure-substructure interactions for drug-drug interaction prediction
10.1093/bib/bbab133 · 2021 · External reference
Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning
10.1038/s43856-024-00486-y · 2024 · External reference
SSF-DDI: A deep learning method utilizing drug sequence and substructure features for drug-drug interaction prediction
10.1186/s12859-024-05654-4 · 2024 · External reference
FG-DDI: Functional group-aware graph neural networks for drug-drug interaction prediction
10.1016/j.jbi.2026.104981 · 2026 · External reference
Multi-view contrastive learning for drug-drug interaction event prediction
10.1109/jbhi.2025.3600045 · 2026 · External reference
LLM-DDI: Leveraging large language models for drug-drug interaction prediction on biomedical knowledge graph
10.1109/jbhi.2025.3585290 · 2026 · External reference
Knowledge graph neural network with spatial-aware capsule for drug-drug interaction prediction
10.1109/jbhi.2024.3419015 · 2025 · External reference
Dual-channel learning framework for drug-drug interaction prediction via relation-aware heterogeneous graph transformer
2024 · External reference
Benchmarking drug-drug interaction prediction methods: A perspective of distribution changes
10.1093/bioinformatics/btaf569 · 2025 · External reference
Predicting the frequencies of drug side effects
10.1038/s41467-020-18305-y · 2020 · External reference
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Assessment of non-linear combination effect terms for drug-drug interactions
10.1007/s10928-016-9490-0 · 2016 · External reference
Using machine learning to identify adverse drug effects posing increased risk to women
10.1016/j.patter.2020.100108 · 2020 · External reference
Distributed Representations of Words and Phrases and their Compositionality.
2013 · External reference
Knowledge graph embedding by translating on hyperplanes
10.1609/aaai.v28i1.8870 · 2014 · External reference
Predicting adverse drug events using pharmacological network models
10.1126/scitranslmed.3002774 · 2011 · External reference
Gathering and exploring scientific knowledge in pharmacovigilance
10.1371/journal.pone.0083016 · 2013 · External reference
Drug repurposing screens and synergistic drug-combinations for infectious diseases
10.1111/bph.13895 · 2018 · External reference
The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets
10.1371/journal.pone.0118432 · 2015 · External reference
Association of coprescription of triptan antimigraine drugs and selective serotonin reuptake inhibitor or selective norepinephrine reuptake inhibitor antidepressants with serotonin syndrome
10.1001/jamaneurol.2017.5144 · 2018 · External reference
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Supporting pharmacovigilance signal validation and prioritization with analyses of routinely collected health data: lessons learned from an EHDEN network study
10.1007/s40264-023-01353-w · 2023 · External reference
Deciphering signatures of mutational processes operative in human cancer
10.1016/j.celrep.2012.12.008 · 2013 · External reference
Signatures of mutational processes in human cancer
10.1038/nature12477 · 2013 · External reference
