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Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite
BACKGROUND: MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunct...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366146/ https://www.ncbi.nlm.nih.gov/pubmed/28340554 http://dx.doi.org/10.1186/s12859-017-1605-0 |
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author | Peng, Hui Lan, Chaowang Zheng, Yi Hutvagner, Gyorgy Tao, Dacheng Li, Jinyan |
author_facet | Peng, Hui Lan, Chaowang Zheng, Yi Hutvagner, Gyorgy Tao, Dacheng Li, Jinyan |
author_sort | Peng, Hui |
collection | PubMed |
description | BACKGROUND: MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics. METHODS AND RESULTS: We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs. CONCLUSIONS: With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1605-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5366146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53661462017-03-28 Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite Peng, Hui Lan, Chaowang Zheng, Yi Hutvagner, Gyorgy Tao, Dacheng Li, Jinyan BMC Bioinformatics Research Article BACKGROUND: MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics. METHODS AND RESULTS: We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs. CONCLUSIONS: With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1605-0) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-24 /pmc/articles/PMC5366146/ /pubmed/28340554 http://dx.doi.org/10.1186/s12859-017-1605-0 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Peng, Hui Lan, Chaowang Zheng, Yi Hutvagner, Gyorgy Tao, Dacheng Li, Jinyan Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite |
title | Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite |
title_full | Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite |
title_fullStr | Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite |
title_full_unstemmed | Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite |
title_short | Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite |
title_sort | cross disease analysis of co-functional microrna pairs on a reconstructed network of disease-gene-microrna tripartite |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366146/ https://www.ncbi.nlm.nih.gov/pubmed/28340554 http://dx.doi.org/10.1186/s12859-017-1605-0 |
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