Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease

Discovering the signaling pathway and regulatory network would provide significant advance in genome-wide understanding of pathogenesis of human diseases. Despite the rich transcriptome data, the limitation for microarray data is unable to detect changes beyond transcriptional level and insufficient...

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Main Authors:	Kong, Wei, Zhang, Jingmao, Mou, Xiaoyang, Yang, Yang
Format:	Online
Language:	English
Published:	Hindawi Publishing Corporation 2014
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4000644/

id	pubmed-4000644
recordtype	oai_dc
spelling	pubmed-40006442014-05-08 Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease Kong, Wei Zhang, Jingmao Mou, Xiaoyang Yang, Yang Research Article Discovering the signaling pathway and regulatory network would provide significant advance in genome-wide understanding of pathogenesis of human diseases. Despite the rich transcriptome data, the limitation for microarray data is unable to detect changes beyond transcriptional level and insufficient in reconstructing pathways and regulatory networks. In our study, protein-protein interaction (PPI) data is introduced to add molecular biological information for predicting signaling pathway of Alzheimer's disease (AD). Combining PPI with gene expression data, significant genes are selected by modified linear regression model firstly. Then, according to the biological researches that inflammation reaction plays an important role in the generation and deterioration of AD, NF-κB (nuclear factor-kappa B), as a significant inflammatory factor, has been selected as the beginning gene of the predicting signaling pathway. Based on that, integer linear programming (ILP) model is proposed to reconstruct the signaling pathway between NF-κB and AD virulence gene APP (amyloid precursor protein). The results identify 6 AD virulence genes included in the predicted inflammatory signaling pathway, and a large amount of molecular biological analysis shows the great understanding of the underlying biological process of AD. Hindawi Publishing Corporation 2014 2014-04-09 /pmc/articles/PMC4000644/ /pubmed/24812571 http://dx.doi.org/10.1155/2014/340758 Text en Copyright © 2014 Wei Kong et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Kong, Wei Zhang, Jingmao Mou, Xiaoyang Yang, Yang
spellingShingle	Kong, Wei Zhang, Jingmao Mou, Xiaoyang Yang, Yang Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease
author_facet	Kong, Wei Zhang, Jingmao Mou, Xiaoyang Yang, Yang
author_sort	Kong, Wei
title	Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease
title_short	Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease
title_full	Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease
title_fullStr	Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease
title_full_unstemmed	Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease
title_sort	integrating gene expression and protein interaction data for signaling pathway prediction of alzheimer's disease
description	Discovering the signaling pathway and regulatory network would provide significant advance in genome-wide understanding of pathogenesis of human diseases. Despite the rich transcriptome data, the limitation for microarray data is unable to detect changes beyond transcriptional level and insufficient in reconstructing pathways and regulatory networks. In our study, protein-protein interaction (PPI) data is introduced to add molecular biological information for predicting signaling pathway of Alzheimer's disease (AD). Combining PPI with gene expression data, significant genes are selected by modified linear regression model firstly. Then, according to the biological researches that inflammation reaction plays an important role in the generation and deterioration of AD, NF-κB (nuclear factor-kappa B), as a significant inflammatory factor, has been selected as the beginning gene of the predicting signaling pathway. Based on that, integer linear programming (ILP) model is proposed to reconstruct the signaling pathway between NF-κB and AD virulence gene APP (amyloid precursor protein). The results identify 6 AD virulence genes included in the predicted inflammatory signaling pathway, and a large amount of molecular biological analysis shows the great understanding of the underlying biological process of AD.
publisher	Hindawi Publishing Corporation
publishDate	2014
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4000644/
_version_	1612082740860026880

Integrating Gene Expression and Protein Interaction Data for Signaling Pathway Prediction of Alzheimer's Disease

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