ArticleBioinformatics (Oxford, England)2016
Predicting synergistic effects between compounds through their structural similarity and effects on transcriptomes.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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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
20 citing papers in PubMed.
- Ecological role of emergent properties in the chemodiversity landscape.Nature ecology & evolution · 2026Review
- Floral scent chemodiversity is associated with high floral visitor but low bacterial richness on flowers.The New phytologist · 2025Article
- Chemotype, maternal genotype, or field neighbors: what influences performance and resource allocation in a perennial plant species the most?Oecologia · 2025Article
- Computational drug repurposing: approaches, evaluation of in silico resources and case studies.Nature reviews. Drug discovery · 2025Review
- Article
- SynerGNet: A Graph Neural Network Model to Predict Anticancer Drug Synergy.Biomolecules · 2024Article
- Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects.Scientific reports · 2024Article
- Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects.Research square · 2023Article
- SynAI: an AI-driven cancer drugs synergism prediction platform.Bioinformatics advances · 2023Article
- Representation of molecules for drug response prediction.Briefings in bioinformatics · 2022Review
- Network Control Models With Personalized Genomics Data for Understanding Tumor Heterogeneity in Cancer.Frontiers in oncology · 2022Review
- Prediction and identification of synergistic compound combinations against pancreatic cancer cells.iScience · 2021Article
- Integrative resource for network-based investigation of COVID-19 combinatorial drug repositioning and mechanism of action.Patterns (New York, N.Y.) · 2021Article
- An update on novel approaches for diagnosis and treatment of SARS-CoV-2 infection.Cell & bioscience · 2021Review
- Synergistic Cytotoxicity of Renieramycin M and Doxorubicin in MCF-7 Breast Cancer Cells.Marine drugs · 2019Article
- Natural Product Target Network Reveals Potential for Cancer Combination Therapies.Frontiers in pharmacology · 2019Article
- Bioactive Compounds ofPolish journal of microbiology · 2019Article
- A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria.Malaria journal · 2018Article
- A New View of Pathway-Driven Drug Resistance in Tumor Proliferation.Trends in pharmacological sciences · 2017Review
- Biomolecular Network-Based Synergistic Drug Combination Discovery.BioMed research international · 2016Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
motivationCombinatorial therapies have been under intensive research for cancer treatment. However, due to the large number of possible combinations among candidate compounds, exhaustive screening is prohibitive. Hence, it is important to develop computational tools that can predict compound combination effects, prioritize combinations and limit the search space to facilitate and accelerate the development of combinatorial therapies.
resultsIn this manuscript we consider the NCI-DREAM Drug Synergy Prediction Challenge dataset to identify features informative about combination effects. Through systematic exploration of differential expression profiles after single compound treatments and comparison of molecular structures of compounds, we found that synergistic levels of combinations are statistically significantly associated with compounds' dissimilarity in structure and similarity in induced gene expression changes. These two types of features offer complementary information in predicting experimentally measured combination effects of compound pairs. Our findings offer insights on the mechanisms underlying different combination effects and may help prioritize promising combinations in the very large search space. AVAILABILITY AND IMPLEMENTATION: The R code for the analysis is available on https://github.com/YiyiLiu1/DrugCombination CONTACT: hongyu.zhao@yale.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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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.