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Identifying pathway modules of tuberculosis in children by analyzing multiple different networks

Tuberculosis (TB), which is caused by the mycobacterium TB, is the major cause of human death worldwide. The aim of this study was to identify the biomarkers involved in child TB. Gene expression data were obtained from the Array Express Archive of Functional Genomics Data. Gene expression data and...

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Autores principales: Cheng, Lu, Han, Yuling, Zhao, Xiuxia, Xu, Xiaoli, Wang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5769296/
https://www.ncbi.nlm.nih.gov/pubmed/29399082
http://dx.doi.org/10.3892/etm.2017.5434
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author Cheng, Lu
Han, Yuling
Zhao, Xiuxia
Xu, Xiaoli
Wang, Jing
author_facet Cheng, Lu
Han, Yuling
Zhao, Xiuxia
Xu, Xiaoli
Wang, Jing
author_sort Cheng, Lu
collection PubMed
description Tuberculosis (TB), which is caused by the mycobacterium TB, is the major cause of human death worldwide. The aim of this study was to identify the biomarkers involved in child TB. Gene expression data were obtained from the Array Express Archive of Functional Genomics Data. Gene expression data and protein-protein interaction (PPI) data were downloaded to construct differential gene co-expression networks (DCNs). The Benjamini-Hochberg algorithm was used to correct the P-value. In total, 3,820 edges (PPIs) and 1,359 nodes (genes) were obtained from the human-related PPIs data and gene expression data at the criteria of absolute value of Pearson's correlation coefficient >0.8. The DCNs were formed by these edges and nodes. Thirteen seed genes were obtained by ranging z-scores. Eight significant multiple different modules were identified from DCNs using the statistical significant test. In conclusion, the seed genes and significant modules constitute potential biomarkers that reveal the underlying mechanisms in child TB. The new identified biomarkers may contribute to an understanding of TB and provide a new therapeutic method for the treatment of TB.
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spelling pubmed-57692962018-02-02 Identifying pathway modules of tuberculosis in children by analyzing multiple different networks Cheng, Lu Han, Yuling Zhao, Xiuxia Xu, Xiaoli Wang, Jing Exp Ther Med Articles Tuberculosis (TB), which is caused by the mycobacterium TB, is the major cause of human death worldwide. The aim of this study was to identify the biomarkers involved in child TB. Gene expression data were obtained from the Array Express Archive of Functional Genomics Data. Gene expression data and protein-protein interaction (PPI) data were downloaded to construct differential gene co-expression networks (DCNs). The Benjamini-Hochberg algorithm was used to correct the P-value. In total, 3,820 edges (PPIs) and 1,359 nodes (genes) were obtained from the human-related PPIs data and gene expression data at the criteria of absolute value of Pearson's correlation coefficient >0.8. The DCNs were formed by these edges and nodes. Thirteen seed genes were obtained by ranging z-scores. Eight significant multiple different modules were identified from DCNs using the statistical significant test. In conclusion, the seed genes and significant modules constitute potential biomarkers that reveal the underlying mechanisms in child TB. The new identified biomarkers may contribute to an understanding of TB and provide a new therapeutic method for the treatment of TB. D.A. Spandidos 2018-01 2017-11-02 /pmc/articles/PMC5769296/ /pubmed/29399082 http://dx.doi.org/10.3892/etm.2017.5434 Text en Copyright: © Cheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Cheng, Lu
Han, Yuling
Zhao, Xiuxia
Xu, Xiaoli
Wang, Jing
Identifying pathway modules of tuberculosis in children by analyzing multiple different networks
title Identifying pathway modules of tuberculosis in children by analyzing multiple different networks
title_full Identifying pathway modules of tuberculosis in children by analyzing multiple different networks
title_fullStr Identifying pathway modules of tuberculosis in children by analyzing multiple different networks
title_full_unstemmed Identifying pathway modules of tuberculosis in children by analyzing multiple different networks
title_short Identifying pathway modules of tuberculosis in children by analyzing multiple different networks
title_sort identifying pathway modules of tuberculosis in children by analyzing multiple different networks
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5769296/
https://www.ncbi.nlm.nih.gov/pubmed/29399082
http://dx.doi.org/10.3892/etm.2017.5434
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