ArticleBioinformatics (Oxford, England)2016
Drug-set enrichment analysis: a novel tool to investigate drug mode of action.
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 39 papers.
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Who cites it
39 citing papers in PubMed, 84 citations in OpenAlex.
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- Drug mechanism enrichment analysis improves prioritization of therapeutics for repurposing.BMC bioinformatics · 2023Article
- Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans.Pharmaceuticals (Basel, Switzerland) · 2023Article
- High-Content Drug Discovery Targeting Molecular Bladder Cancer Subtypes.International journal of molecular sciences · 2022Article
- Tissue-specific identification of multi-omics features for pan-cancer drug response prediction.iScience · 2022Article
- From GWAS to drug screening: repurposing antipsychotics for glioblastoma.Journal of translational medicine · 2022Article
- Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation.Briefings in bioinformatics · 2022Article
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- Pleiotropic effects of telomere length loci with brain morphology and brain tissue expression.Human molecular genetics · 2021Article
- Automatic identification of small molecules that promote cell conversion and reprogramming.Stem cell reports · 2021Article
- Drugmonizome and Drugmonizome-ML: integration and abstraction of small molecule attributes for drug enrichment analysis and machine learning.Database : the journal of biological databases and curation · 2021Article
- The anti-tumour activity of DNA methylation inhibitor 5-aza-2'-deoxycytidine is enhanced by the common analgesic paracetamol through induction of oxidative stress.Cancer letters · 2021Article
- Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach.BMC bioinformatics · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
motivationAutomated screening approaches are able to rapidly identify a set of small molecules inducing a desired phenotype from large small-molecule libraries. However, the resulting set of candidate molecules is usually very diverse pharmacologically, thus little insight on the shared mechanism of action (MoA) underlying their efficacy can be gained.
resultsWe introduce a computational method (Drug-Set Enrichment Analysis-DSEA) based on drug-induced gene expression profiles, which is able to identify the molecular pathways that are targeted by most of the drugs in the set. By diluting drug-specific effects unrelated to the phenotype of interest, DSEA is able to highlight phenotype-specific pathways, thus helping to formulate hypotheses on the MoA shared by the drugs in the set. We validated the method by analysing five different drug-sets related to well-known pharmacological classes. We then applied DSEA to identify the MoA shared by drugs known to be partially effective in rescuing mutant cystic fibrosis transmembrane conductance regulator (CFTR) gene function in Cystic Fibrosis. AVAILABILITY AND IMPLEMENTATION: The method is implemented as an online web tool publicly available at http://dsea.tigem.it. CONTACT: dibernardo@tigem.it 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.