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Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease
In order to understand the pathogenic factors that initiate the processes of Alzheimer's disease (AD), a method of inference of multiple differential modules (iMDM) to conduct analysis was performed on the gene expression profile of AD. A total of 11,089 genes and 588,391 interactions were gain...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5613183/ https://www.ncbi.nlm.nih.gov/pubmed/28966679 http://dx.doi.org/10.3892/etm.2017.4905 |
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author | Wang, Zhengling Yan, Xinling Zhao, Chenghua |
author_facet | Wang, Zhengling Yan, Xinling Zhao, Chenghua |
author_sort | Wang, Zhengling |
collection | PubMed |
description | In order to understand the pathogenic factors that initiate the processes of Alzheimer's disease (AD), a method of inference of multiple differential modules (iMDM) to conduct analysis was performed on the gene expression profile of AD. A total of 11,089 genes and 588,391 interactions were gained based on the gene expression profile and protein-protein interaction network. Subsequently, three differential co-expression networks (DCNs) were constructed with the same nodes but different interactions, and eight multiple differential modules (M-DMs) were identified. Furthermore, by performing Module Connectivity Dynamic Score to quantify the change in the connectivity of component modules, two M-DMs were identified: Module 1 (P=0.0419) and 2 (P=0.0419; adjusted, P≤0.05). Finally, hub genes of MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 were gained via topological analysis conducted on the 2 M-DMs. In conclusion, the method of iMDM was suitable for conducting analysis on AD. By applying iMDM, 2 M-DMs were successfully identified and the MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 genes were predicted to be important during the occurrence and development of AD. |
format | Online Article Text |
id | pubmed-5613183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-56131832017-09-29 Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease Wang, Zhengling Yan, Xinling Zhao, Chenghua Exp Ther Med Articles In order to understand the pathogenic factors that initiate the processes of Alzheimer's disease (AD), a method of inference of multiple differential modules (iMDM) to conduct analysis was performed on the gene expression profile of AD. A total of 11,089 genes and 588,391 interactions were gained based on the gene expression profile and protein-protein interaction network. Subsequently, three differential co-expression networks (DCNs) were constructed with the same nodes but different interactions, and eight multiple differential modules (M-DMs) were identified. Furthermore, by performing Module Connectivity Dynamic Score to quantify the change in the connectivity of component modules, two M-DMs were identified: Module 1 (P=0.0419) and 2 (P=0.0419; adjusted, P≤0.05). Finally, hub genes of MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 were gained via topological analysis conducted on the 2 M-DMs. In conclusion, the method of iMDM was suitable for conducting analysis on AD. By applying iMDM, 2 M-DMs were successfully identified and the MDH1, NDUFAB1, NDUFB5, DDX1 and MRPS35 genes were predicted to be important during the occurrence and development of AD. D.A. Spandidos 2017-10 2017-08-08 /pmc/articles/PMC5613183/ /pubmed/28966679 http://dx.doi.org/10.3892/etm.2017.4905 Text en Copyright: © Wang 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 Wang, Zhengling Yan, Xinling Zhao, Chenghua Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease |
title | Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease |
title_full | Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease |
title_fullStr | Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease |
title_full_unstemmed | Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease |
title_short | Dynamical differential networks and modules inferring disrupted genes associated with the progression of Alzheimer's disease |
title_sort | dynamical differential networks and modules inferring disrupted genes associated with the progression of alzheimer's disease |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5613183/ https://www.ncbi.nlm.nih.gov/pubmed/28966679 http://dx.doi.org/10.3892/etm.2017.4905 |
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