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Bioinformatics analysis to screen for genes related to myocardial infarction
Myocardial infarction (MI) is an acute and persistent myocardial ischemia caused by coronary artery disease. This study screened potential genes related to MI. Three gene expression datasets related to MI were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589498/ https://www.ncbi.nlm.nih.gov/pubmed/36299582 http://dx.doi.org/10.3389/fgene.2022.990888 |
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author | Yang, Liting Pan, Xuyang Zhang, Ying Zhao, Dongsheng Wang, Liang Yuan, Guoliang Zhou, Changgao Li, Tao Li, Wei |
author_facet | Yang, Liting Pan, Xuyang Zhang, Ying Zhao, Dongsheng Wang, Liang Yuan, Guoliang Zhou, Changgao Li, Tao Li, Wei |
author_sort | Yang, Liting |
collection | PubMed |
description | Myocardial infarction (MI) is an acute and persistent myocardial ischemia caused by coronary artery disease. This study screened potential genes related to MI. Three gene expression datasets related to MI were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened using the MetaDE package. Afterward, the modules and genes closely related to MI were screened and a gene co-expression network was constructed. A support vector machine (SVM) classification model was then constructed based on the GSE61145 dataset using the e1071 package in R. A total of 98 DEGs were identified in the MI samples. Next, three modules associated with MI were screened and an SVM classification model involving seven genes was constructed. Among them, BCL6, CEACAM8, and CUGBP2 showed co-interactions in the gene co-expression network. Therefore, ACOX1, BCL6, CEACAM8, and CUGBP2, in addition to GPX7, might be feature genes related to MI. |
format | Online Article Text |
id | pubmed-9589498 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95894982022-10-25 Bioinformatics analysis to screen for genes related to myocardial infarction Yang, Liting Pan, Xuyang Zhang, Ying Zhao, Dongsheng Wang, Liang Yuan, Guoliang Zhou, Changgao Li, Tao Li, Wei Front Genet Genetics Myocardial infarction (MI) is an acute and persistent myocardial ischemia caused by coronary artery disease. This study screened potential genes related to MI. Three gene expression datasets related to MI were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened using the MetaDE package. Afterward, the modules and genes closely related to MI were screened and a gene co-expression network was constructed. A support vector machine (SVM) classification model was then constructed based on the GSE61145 dataset using the e1071 package in R. A total of 98 DEGs were identified in the MI samples. Next, three modules associated with MI were screened and an SVM classification model involving seven genes was constructed. Among them, BCL6, CEACAM8, and CUGBP2 showed co-interactions in the gene co-expression network. Therefore, ACOX1, BCL6, CEACAM8, and CUGBP2, in addition to GPX7, might be feature genes related to MI. Frontiers Media S.A. 2022-10-10 /pmc/articles/PMC9589498/ /pubmed/36299582 http://dx.doi.org/10.3389/fgene.2022.990888 Text en Copyright © 2022 Yang, Pan, Zhang, Zhao, Wang, Yuan, Zhou, Li and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Yang, Liting Pan, Xuyang Zhang, Ying Zhao, Dongsheng Wang, Liang Yuan, Guoliang Zhou, Changgao Li, Tao Li, Wei Bioinformatics analysis to screen for genes related to myocardial infarction |
title | Bioinformatics analysis to screen for genes related to myocardial infarction |
title_full | Bioinformatics analysis to screen for genes related to myocardial infarction |
title_fullStr | Bioinformatics analysis to screen for genes related to myocardial infarction |
title_full_unstemmed | Bioinformatics analysis to screen for genes related to myocardial infarction |
title_short | Bioinformatics analysis to screen for genes related to myocardial infarction |
title_sort | bioinformatics analysis to screen for genes related to myocardial infarction |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589498/ https://www.ncbi.nlm.nih.gov/pubmed/36299582 http://dx.doi.org/10.3389/fgene.2022.990888 |
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