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

Y Liu, F Bai, Z Tang, N Liu, Q Liu - BMC Cardiovascular Disorders, 2021 - Springer
Background Atrial fibrillation (AF) is the most common arrhythmia with poorly understood
mechanisms. We aimed to investigate the biological mechanism of AF and to discover …

Identification of potential crucial genes in atrial fibrillation: a bioinformatic analysis

J Zhang, X Huang, X Wang, Y Gao, L Liu, Z Li… - BMC medical …, 2020 - Springer
Background Atrial fibrillation (AF) is at least partially heritable, affecting 2–3% of the
population in Europe and the USA. However, a substantial proportion of heritability is still …

Identification of differentially expressed genes and pathways in human atrial fibrillation by bioinformatics analysis

D Pan, Y Zhou, S Xiao, Y Hu, C Huan… - … Journal of General …, 2022 - Taylor & Francis
Introduction Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, but the
molecular mechanisms underlying AF are not known. We aimed to identify the pivotal genes …

[PDF][PDF] Identification of potential novel biomarkers and therapeutic targets involved in human atrial fibrillation based on bioinformatics analysis

G Fan, J Wei - Kardiologia Polska (Polish Heart Journal), 2020 - journals.viamedica.pl
Background: Atrial fibrillation (AF) is the most common arrhythmia. However, exact
molecular mechanism of AF remains unclear. Aims: Our study aimed to identify underlying …

Meta-analysis of transcriptomic data reveals pathophysiological modules involved with atrial fibrillation

R Haas Bueno, M Recamonde-Mendoza - Molecular Diagnosis & Therapy, 2020 - Springer
Background Atrial fibrillation (AF) is a complex disease and affects millions of people around
the world. The biological mechanisms that are involved with AF are complex and still need to …

Integrative identification of immune-related key genes in atrial fibrillation using weighted gene coexpression network analysis and machine learning

PF Zheng, LZ Chen, P Liu, ZY Liu… - Frontiers in …, 2022 - frontiersin.org
Background The immune system significantly participates in the pathologic process of atrial
fibrillation (AF). However, the molecular mechanisms underlying this participation are not …

[HTML][HTML] Potential target genes in the development of atrial fibrillation: A comprehensive bioinformatics analysis

L Liu, Y Yu, L Hu, Q Dong, F Hu, L Zhu… - … Medical Journal of …, 2021 - ncbi.nlm.nih.gov
Background Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although it is
not life-threatening, the accompanying rapid and irregular ventricular rate can lead to …

Analysis of potential genetic biomarkers using machine learning methods and immune infiltration regulatory mechanisms underlying atrial fibrillation

LD Wu, F Li, JY Chen, J Zhang, LL Qian… - BMC Medical …, 2022 - Springer
Objective We aimed to screen out biomarkers for atrial fibrillation (AF) based on machine
learning methods and evaluate the degree of immune infiltration in AF patients in detail …

Bioinformatic analysis for the identification of potential gene interactions and therapeutic targets in atrial fibrillation

S Yu, J Yu, Y Guo, Y Chu, H Zhang - bioRxiv, 2020 - biorxiv.org
Background Atrial fibrillation (AF) is the most prevalent tachycardia. The major injuries
caused by AF are systemic embolism and heart failure. Although AF therapies have evolved …

[HTML][HTML] Weighted gene co‑expression network analysis to identify key modules and hub genes associated with atrial fibrillation

W Li, L Wang, Y Wu, Z Yuan… - … Journal of Molecular …, 2020 - spandidos-publications.com
Atrial fibrillation (AF) is the most common form of cardiac arrhythmia and significantly
increases the risks of morbidity, mortality and health care expenditure; however, treatment …