ArticleFrontiers in genetics2022
miRModuleNet: Detecting miRNA-mRNA Regulatory Modules.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 39 citations in OpenAlex.
- Regulatory Genetic Networks by microRNAs: Exploring Genomic Signatures in Cervical Cancer.Biomedicines · 2025Review
- Effect of the MIAT/microRNA 130a-3p/Pdgfra axis on retinal microglia activation in mice with chronic retinal hypoperfusion injury.Cell biology and toxicology · 2025Article
- RCE-IFE: recursive cluster elimination with intra-cluster feature elimination.PeerJ. Computer science · 2025Article
- PDLIM1, a novel miR-3940-5p target, regulates the malignant progression of diffuse large B-cell lymphoma.Cancer biology & therapy · 2024Article
- Advancing miRNA cancer research through artificial intelligence: from biomarker discovery to therapeutic targeting.Medical oncology (Northwood, London, England) · 2024Review
- Topic selection for text classification using ensemble topic modeling with grouping, scoring, and modeling approach.Scientific reports · 2024Article
- miRNAs in Heart Development and Disease.International journal of molecular sciences · 2024Review
- PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach.BMC bioinformatics · 2023Article
- Review
- GeNetOntology: identifying affected gene ontology terms via grouping, scoring, and modeling of gene expression data utilizing biological knowledge-based machine learning.Frontiers in genetics · 2023Article
- microBiomeGSM: the identification of taxonomic biomarkers from metagenomic data using grouping, scoring and modeling (G-S-M) approach.Frontiers in microbiology · 2023Article
- TextNetTopics Pro, a topic model-based text classification for short text by integration of semantic and document-topic distribution information.Frontiers in genetics · 2023Article
- Invention of 3Mint for feature grouping and scoring in multi-omics.Frontiers in genetics · 2023Article
- GediNET for discovering gene associations across diseases using knowledge based machine learning approach.Scientific reports · 2022Article
- A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective.International journal of molecular sciences · 2022Review
- TextNetTopics: Text Classification Based Word Grouping as Topics and Topics' Scoring.Frontiers in genetics · 2022Article
- miRdisNET: Discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increasing evidence that microRNAs (miRNAs) play a key role in carcinogenesis has revealed the need for elucidating the mechanisms of miRNA regulation and the roles of miRNAs in gene-regulatory networks. A better understanding of the interactions between miRNAs and their mRNA targets will provide a better understanding of the complex biological processes that occur during carcinogenesis. Increased efforts to reveal these interactions have led to the development of a variety of tools to detect and understand these interactions. We have recently described a machine learning approach miRcorrNet, based on grouping and scoring (ranking) groups of genes, where each group is associated with a miRNA and the group members are genes with expression patterns that are correlated with this specific miRNA. The miRcorrNet tool requires two types of -omics data, miRNA and mRNA expression profiles, as an input file. In this study we describe miRModuleNet, which groups mRNA (genes) that are correlated with each miRNA to form a
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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.