Bioinformatic Analysis of the Association Between Myocardial Disease and Diesel Particulate Matter

Kyoung Jin Nho*; Jae Hoon Shin

**Kyoung Jin Nho* and Jae Hoon Shin**

Volume4-Issue4
Dates: Received: 2023-03-24 | Accepted: 2023-04-03 | Published: 2023-04-04
Pages: 590-599

Abstract

The etiological connection between Diesel Particulate Matter (DPM) and heart failure is unclear, despite the fact that multiple experimental studies have found a strong correlation between DPM and heart failure. We investigated the correlation between DPM and myocardial infarction using biological big data. Distinct gene expression profiles related to DPM and myocardial infarction were obtained from open-access genome databases, and a network analysis software was used to investigate their interaction. We investigated the detrimental effects of DPM on cardiac cells to understand the association between them. The putative signaling networks of 33 genes with differential expression were identified and studied. In addition to increasing the prediction accuracy, our study used experimental validation and literature-based analysis to enhance the knowledge of the mechanisms underlying DPM-related cardiac disease.

FullText HTML FullText PDF DOI: 10.37871/jbres1714

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How to cite this article

Nho KJ, Shin JH. Bioinformatic Analysis of the Association Between Myocardial Disease and Diesel Particulate Matter. 2023 Apr 04; 4(4): 590-599. doi: 10.37871/jbres1714, Article ID: JBRES1714, Available at: https://www.jelsciences.com/articles/ jbres1714.pdf

Subject area(s)

Bioinformatics

Biology

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