Title
Study on the miRNA-mediated regulatory network in the heart adjacent tissues of patients with tetralogy of Fallot
Abstract
When Tetralogy of Fallot (TOF) disease occurs, the miRNA expression profile of the diseased tissues will change significantly, showing a disease-specific expression profile. However, the molecular mechanisms of its pathogenesis and development are still unclear. In this article, we selected the data set related to TOF disease and screened out the 149 differentially expressed (DE) miRNAs in the right ventricular outflow tract (RVOT) myocardial tissue and the 38 DE miRNAs expressed in the right ventricular (RV) myocardial tissue, as a result, it was found that two different miRNAs from adjacent tissues combined with target genes to construct a regulatory network. Research on the network and that these two networks meet the characteristics of a scale-free network. The functional analysis of the 64 target genes shared by the two adjacent regulatory networks showed that they were associated with TOF disease. 34 hub nodes were found in the RV myocardial tissue. 15 nodes were found in RVOT myocardial tissue. In the discussion section, we discussed the relationship between genes and drugs in the hub node, and analyzed the potential effects of three potential drugs on TOF disease by regulating the STAT3 gene. Therefore, this article analyzes the molecular level changes of the two types of myocardial tissues through miRNA-mediated regulatory networks, including the biological functions, signal transmission and network characteristics of adjacent areas and important nodules in TOF disease. Exploring the relationship between hub nodes and drug target.
Year
DOI
Venue
2020
10.1109/BIBE50027.2020.00015
2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)
Keywords
DocType
ISSN
miRNA,Tetralogy of Fallot,regulatory network,right ventricular,right ventricular outflow tract
Conference
2159-5410
ISBN
Citations 
PageRank 
978-1-7281-9575-9
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Guangbin Wang153.67
Nini Rao28511.36
Changlong Dong300.34
K. Felix Biwott400.34
Wei Zeng500.34
Fenglin Gao600.34