Article

Integrated Analysis of microRNA-mRNA Network Predicts Potential Regulators of Atrial Fibrillation in Human

2022-02-07

Abstract excerpt

Atrial fibrillation (AF) is a form of sustained cardiac arrhythmia and microRNAs (miRs) play crucial roles in pathophysiology of AF. To identify novel miR-mRNA pairs, we performed RNAseq from atrial biopsies of AF and non-AF patients. Differentially expressed miRs (11-down and 9-up) and mRNAs (95-up and 82-down) were identified and hierarchically clustered in a heat-map. Subsequently, GO, KEGG, and GSEA analyses w...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 048bb518-2928-56e0-9b9e-e9d038a6b09e
DOI: 10.20944/preprints202202.0103.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Integrated Analysis of microRNA-mRNA Network Predicts Potential Regulators of Atrial Fibrillation in HumanDOI 10.20944/preprints202202.0103.v1Read

Identification of key genes in atrial fibrillation using bioinformatics analysis.Semantic proximity Read

Identifying Pivotal microRNAs and Target Genes Associated With the Pathogenesis of Atrial FibrillationSemantic proximity Read

Identification of potential novel biomarkers and therapeutic targets involved in human atrial fibrillation based on bioinformatics analysisSemantic proximity Read

RNA Sequence Analysis of Differentially Expressed Genes in Left Atrial Appendage ThrombusSemantic proximity Read

A bioinformatics-based analysis of chromatin regulators in atrial fibrillation uncovers potential novel biomarkers and immune infiltration characteristicsSemantic proximity Read

MicroRNA Regulatory Network Revealing the Mechanism of Inflammation in Atrial FibrillationSemantic proximity Read

Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics AnalysisSemantic proximity Read

Identification of microRNAs enriched in exosomes in human pericardial fluid of patients with atrial fibrillation based on bioinformatic analysisSemantic proximity Read

Differential Circular RNA Expression Analysis for Screening the Potential Biomarkers in Atrial Fibrillation PatientsSemantic proximity Read

Analysis of the Potential Role of Key Genes in Atrial Fibrillation Based on Bioinformatics ApproachSemantic proximity Read

Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart diseaseSemantic proximity Read

Long non-coding RNA expression profile in atrial fibrillation.Semantic proximity Read