ArticleBioinformatics (Oxford, England)2024
Dual-view jointly learning improves personalized drug synergy prediction.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Momentum contrast-enhanced multimodal representation learning for drug synergy prediction.Bioinformatics (Oxford, England) · 2026Article
- Unified heterogeneity-aware benchmark of drug synergy prediction: a cross-study analysis of traditional machine learning and graph deep learning models.Journal of cheminformatics · 2026Article
- Interpretable graph deep learning framework for drug synergy prediction by integrating functional and clinical similarities.NPJ digital medicine · 2026Article
- DeepDrugs: a mechanism-aware tri-linear attention framework for synergistic drug-combination prediction.Briefings in bioinformatics · 2026Article
- PDTSyn: a parameter-decomposed transformer for domain-generalized cell line-aware drug synergy prediction.Briefings in bioinformatics · 2026Article
- One-hot news: drug synergy models shortcut molecular features.Bioinformatics (Oxford, England) · 2026Article
- UniSyn: a multi-modal framework with knowledge transfer for anti-cancer drug synergy prediction.Genome biology · 2026Article
- Machine learning models for drug-drug interaction prediction from computational discovery to clinical application.NPJ digital medicine · 2026Review
- A review of deep learning approaches for drug synergy prediction in cancer.npj drug discovery · 2025Review
- SynergyImage: image-based model for drug combinations synergy score prediction.BMC bioinformatics · 2025Article
- Few-shot drug synergy prediction via rapid cross-tier adaptation meta-optimization.Briefings in bioinformatics · 2025Article
- SenolyticSynergy: An Attention-Based Network for Discovering Novel Senolytic Combinations via Human Aging Genomics.International journal of molecular sciences · 2025Article
- Machine Learning for Multi-Target Drug Discovery: Challenges and Opportunities in Systems Pharmacology.Pharmaceutics · 2025Review
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Authors and funding
7 authors.
Funding
Abstract
motivationAccurate and robust estimation of the synergistic drug combination is important for medicine precision. Although some computational methods have been developed, some predictions are still unreliable especially for the cross-dataset predictions, due to the complex mechanism of drug combinations and heterogeneity of cancer samples.
resultsWe have proposed JointSyn that utilizes dual-view jointly learning to predict sample-specific effects of drug combination from drug and cell features. JointSyn outperforms existing state-of-the-art methods in predictive accuracy and robustness across various benchmarks. Each view of JointSyn captures drug synergy-related characteristics and makes complementary contributes to the final prediction of the drug combination. Moreover, JointSyn with fine-tuning improves its generalization ability to predict a novel drug combination or cancer sample using a small number of experimental measurements. We also used JointSyn to generate an estimated atlas of drug synergy for pan-cancer and explored the differential pattern among cancers. These results demonstrate the potential of JointSyn to predict drug synergy, supporting the development of personalized combinatorial therapies. AVAILABILITY AND IMPLEMENTATION: Source code and data are available at https://github.com/LiHongCSBLab/JointSyn.
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