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Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes

BACKGROUND: MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases...

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Autores principales: Shi, Hongbo, Xu, Juan, Zhang, Guangde, Xu, Liangde, Li, Chunquan, Wang, Li, Zhao, Zheng, Jiang, Wei, Guo, Zheng, Li, Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4124764/
https://www.ncbi.nlm.nih.gov/pubmed/24103777
http://dx.doi.org/10.1186/1752-0509-7-101
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author Shi, Hongbo
Xu, Juan
Zhang, Guangde
Xu, Liangde
Li, Chunquan
Wang, Li
Zhao, Zheng
Jiang, Wei
Guo, Zheng
Li, Xia
author_facet Shi, Hongbo
Xu, Juan
Zhang, Guangde
Xu, Liangde
Li, Chunquan
Wang, Li
Zhao, Zheng
Jiang, Wei
Guo, Zheng
Li, Xia
author_sort Shi, Hongbo
collection PubMed
description BACKGROUND: MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed. RESULTS: We developed a computational framework to identify miRNA-disease associations by performing random walk analysis, and focused on the functional link between miRNA targets and disease genes in protein-protein interaction (PPI) networks. Furthermore, a bipartite miRNA-disease network was constructed, from which several miRNA-disease co-regulated modules were identified by hierarchical clustering analysis. Our approach achieved satisfactory performance in identifying known cancer-related miRNAs for nine human cancers with an area under the ROC curve (AUC) ranging from 71.3% to 91.3%. By systematically analyzing the global properties of the miRNA-disease network, we found that only a small number of miRNAs regulated genes involved in various diseases, genes associated with neurological diseases were preferentially regulated by miRNAs and some immunological diseases were associated with several specific miRNAs. We also observed that most diseases in the same co-regulated module tended to belong to the same disease category, indicating that these diseases might share similar miRNA regulatory mechanisms. CONCLUSIONS: In this study, we present a computational framework to identify miRNA-disease associations, and further construct a bipartite miRNA-disease network for systematically analyzing the global properties of miRNA regulation of disease genes. Our findings provide a broad perspective on the relationships between miRNAs and diseases and could potentially aid future research efforts concerning miRNA involvement in disease pathogenesis.
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spelling pubmed-41247642014-08-12 Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes Shi, Hongbo Xu, Juan Zhang, Guangde Xu, Liangde Li, Chunquan Wang, Li Zhao, Zheng Jiang, Wei Guo, Zheng Li, Xia BMC Syst Biol Research Article BACKGROUND: MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed. RESULTS: We developed a computational framework to identify miRNA-disease associations by performing random walk analysis, and focused on the functional link between miRNA targets and disease genes in protein-protein interaction (PPI) networks. Furthermore, a bipartite miRNA-disease network was constructed, from which several miRNA-disease co-regulated modules were identified by hierarchical clustering analysis. Our approach achieved satisfactory performance in identifying known cancer-related miRNAs for nine human cancers with an area under the ROC curve (AUC) ranging from 71.3% to 91.3%. By systematically analyzing the global properties of the miRNA-disease network, we found that only a small number of miRNAs regulated genes involved in various diseases, genes associated with neurological diseases were preferentially regulated by miRNAs and some immunological diseases were associated with several specific miRNAs. We also observed that most diseases in the same co-regulated module tended to belong to the same disease category, indicating that these diseases might share similar miRNA regulatory mechanisms. CONCLUSIONS: In this study, we present a computational framework to identify miRNA-disease associations, and further construct a bipartite miRNA-disease network for systematically analyzing the global properties of miRNA regulation of disease genes. Our findings provide a broad perspective on the relationships between miRNAs and diseases and could potentially aid future research efforts concerning miRNA involvement in disease pathogenesis. BioMed Central 2013-10-08 /pmc/articles/PMC4124764/ /pubmed/24103777 http://dx.doi.org/10.1186/1752-0509-7-101 Text en Copyright © 2013 Shi et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Shi, Hongbo
Xu, Juan
Zhang, Guangde
Xu, Liangde
Li, Chunquan
Wang, Li
Zhao, Zheng
Jiang, Wei
Guo, Zheng
Li, Xia
Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
title Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
title_full Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
title_fullStr Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
title_full_unstemmed Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
title_short Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
title_sort walking the interactome to identify human mirna-disease associations through the functional link between mirna targets and disease genes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4124764/
https://www.ncbi.nlm.nih.gov/pubmed/24103777
http://dx.doi.org/10.1186/1752-0509-7-101
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