ArticleCPT: pharmacometrics & systems pharmacology2015
DIGRE: Drug-Induced Genomic Residual Effect Model for Successful Prediction of Multidrug Effects.
Article in CPT: pharmacometrics & systems pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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
20 citing papers in PubMed, 39 citations in OpenAlex.
- Article
- Network-based estimation of therapeutic efficacy and adverse reaction potential for prioritisation of anti-cancer drug combinations.Computational and structural biotechnology journal · 2025Article
- Fine tuning a logical model of cancer cells to predict drug synergies: combining manual curation and automated parameterization.Frontiers in systems biology · 2023Article
- From cell lines to cancer patients: personalized drug synergy prediction.Bioinformatics (Oxford, England) · 2022Article
- Anticancer drug synergy prediction in understudied tissues using transfer learning.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Probing Synergistic Targets by Natural Compounds for Hepatocellular Carcinoma.Frontiers in cell and developmental biology · 2021Article
- Article
- Article
- Essentiality and Transcriptome-Enriched Pathway Scores Predict Drug-Combination Synergy.Biology · 2020Article
- Driver network as a biomarker: systematic integration and network modeling of multi-omics data to derive driver signaling pathways for drug combination prediction.Bioinformatics (Oxford, England) · 2019Article
- DIGREM: an integrated web-based platform for detecting effective multi-drug combinations.Bioinformatics (Oxford, England) · 2019Article
- Article
- Article
- DeepSynergy: predicting anti-cancer drug synergy with Deep Learning.Bioinformatics (Oxford, England) · 2018Article
- The Prediction of Drug-Disease Correlation Based on Gene Expression Data.BioMed research international · 2018Article
- Computational models for predicting drug responses in cancer research.Briefings in bioinformatics · 2017Review
- Informatics Approaches for Predicting, Understanding, and Testing Cancer Drug Combinations.Methods in molecular biology (Clifton, N.J.) · 2017Article
- Predicting synergistic effects between compounds through their structural similarity and effects on transcriptomes.Bioinformatics (Oxford, England) · 2016Article
- A simple gene set-based method accurately predicts the synergy of drug pairs.BMC systems biology · 2016Article
- Biomolecular Network-Based Synergistic Drug Combination Discovery.BioMed research international · 2016Review
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
Multidrug regimens are a promising strategy for improving therapeutic efficacy and reducing side effects, especially for complex disorders such as cancer. However, the use of multidrug therapies is very challenging, due to a lack of understanding of the mechanisms of drug interactions. We herein present a novel computational approach-Drug-Induced Genomic Residual Effect (DIGRE) Computational Model-to predict drug combination effects by explicitly modeling drug response curves and gene expression changes after drug treatments. The prediction performance of DIGRE was evaluated using two datasets: (i) OCI-LY3 B-lymphoma cells treated with 14 different drugs and (ii) MCF breast cancer cells treated with combinations of gefitinib and docetaxel at different doses. In both datasets, the predicted drug combination effects significantly correlated with the experimental results. The results indicated the model was useful in predicting drug combination effects, which may greatly facilitate the discovery of new, effective multidrug therapies.
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.