ArticleBioinformatics (Oxford, England)2018
EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to improve prediction accuracy.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- PGM1 deficiency is linked to sarcomeric and mitochondrial dysfunction in patient-derived iPSC-cardiomyocytes.Journal of translational medicine · 2026Article
- A computational genetic- and transcriptomics-based study nominates drug repurposing candidates for the treatment of chronic pain.EBioMedicine · 2025Article
- Redefining Breast Cancer Care by Harnessing Computational Drug Repositioning.Medicina (Kaunas, Lithuania) · 2025Review
- Predicting disease-overarching therapeutic approaches for Congenital Disorders of Glycosylation using multi-OMICS.bioRxiv : the preprint server for biology · 2025Article
- Integrative transcriptome-based drug repurposing in tuberculosis.bioRxiv : the preprint server for biology · 2025Article
- Functional genomics pipeline identifies CRL4 inhibition for the treatment of ovarian cancer.Clinical and translational medicine · 2025Article
- Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery.Genome medicine · 2025Article
- iDOMO: identification of drug combinations via multi-set operations for treating diseases.Briefings in bioinformatics · 2024Article
- Limb reduction in an Esco2 cohesinopathy mouse model is mediated by p53-dependent apoptosis and vascular disruption.Nature communications · 2024Article
- Signature reversion of three disease-associated gene signatures prioritizes cancer drug repurposing candidates.FEBS open bio · 2024Article
- Pinpointing the integration of artificial intelligence in liver cancer immune microenvironment.Frontiers in immunology · 2024Review
- Multi-omics-based analysis of high grade serous ovarian cancer subtypes reveals distinct molecular processes linked to patient prognosis.FEBS open bio · 2023Article
- Identification of significant gene expression changes in multiple perturbation experiments using knockoffs.Briefings in bioinformatics · 2023Article
- Article
- Considerations and challenges for sex-aware drug repurposing.Biology of sex differences · 2022Review
- A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer.eLife · 2022Article
- Article
- Drug Repurposing Using Modularity Clustering in Drug-Drug Similarity Networks Based on Drug-Gene Interactions.Pharmaceutics · 2021Article
- Reconciling multiple connectivity scores for drug repurposing.Briefings in bioinformatics · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Motivation: Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify the therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods. Results: We first designed an expression weighted cosine (EWCos) method to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed ensemble of multiple drug repositioning approaches (EMUDRA) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs. Availability and implementation: The EMUDRA R package is available at doi: 10.7303/syn11510888. Supplementary 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.