ArticleBMC bioinformatics2021
CeNet Omnibus: an R/Shiny application to the construction and analysis of competing endogenous RNA network.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- The Multi-Target lncRNA-miRNA-mRNA TRIAD in Pancreatic Cancer Diagnosis and Therapy.International journal of molecular sciences · 2026Review
- PESSA: A web tool for pathway enrichment score-based survival analysis in cancer.PLoS computational biology · 2024Article
- ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation.Frontiers in molecular biosciences · 2022Article
- Feature Genes in Neuroblastoma Distinguishing High-Risk and Non-high-Risk Neuroblastoma Patients: Development and Validation Combining Random Forest With Artificial Neural Network.Frontiers in medicine · 2022Article
- miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation.Bioinformatics advances · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundThe competing endogenous RNA (ceRNA) regulation is a newly discovered post-transcriptional regulation mechanism and plays significant roles in physiological and pathological progress. CeRNA networks provide global views to help understand the regulation of ceRNAs. CeRNA networks have been widely used to detect survival biomarkers, select candidate regulators of disease genes, and predict long noncoding RNA functions. However, there is no software platform to provide overall functions from the construction to analysis of ceRNA networks.
resultsTo fill this gap, we introduce CeNet Omnibus, an R/Shiny application, which provides a unified framework for the construction and analysis of ceRNA network. CeNet Omnibus enables users to select multiple measurements, such as Pearson correlation coefficient (PCC), mutual information (MI), and liquid association (LA), to identify ceRNA pairs and construct ceRNA networks. Furthermore, CeNet Omnibus provides a one-stop solution to analyze the topological properties of ceRNA networks, detect modules, and perform gene enrichment analysis and survival analysis. CeNet Omnibus intends to cover comprehensiveness, high efficiency, high expandability, and user customizability, and it also offers a web-based user-friendly interface to users to obtain the output intuitionally.
conclusionCeNet Omnibus is a comprehensive platform for the construction and analysis of ceRNA networks. It is highly customizable and outputs the results in intuitive and interactive. We expect that CeNet Omnibus will assist researchers to understand the property of ceRNA networks and associated biological phenomena. CeNet Omnibus is an R/Shiny application based on the Shiny framework developed by RStudio. The R package and detailed tutorial are available on our GitHub page with the URL https://github.com/GaoLabXDU/CeNetOmnibus .
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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.