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Inferring pleiotropy by network analysis: linked diseases in the human PPI network
BACKGROUND: Earlier, we identified proteins connecting different disease proteins in the human protein-protein interaction network and quantified their mediator role. An analysis of the networks of these mediators shows that proteins connecting heart disease and diabetes largely overlap with the one...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231966/ https://www.ncbi.nlm.nih.gov/pubmed/22034985 http://dx.doi.org/10.1186/1752-0509-5-179 |
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author | Nguyen, Thanh-Phuong Liu, Wei-chung Jordán, Ferenc |
author_facet | Nguyen, Thanh-Phuong Liu, Wei-chung Jordán, Ferenc |
author_sort | Nguyen, Thanh-Phuong |
collection | PubMed |
description | BACKGROUND: Earlier, we identified proteins connecting different disease proteins in the human protein-protein interaction network and quantified their mediator role. An analysis of the networks of these mediators shows that proteins connecting heart disease and diabetes largely overlap with the ones connecting heart disease and obesity. RESULTS: We quantified their overlap, and based on the identified topological patterns, we inferred the structural disease-relatedness of several proteins. Literature data provide a functional look of them, well supporting our findings. For example, the inferred structurally important role of the PDZ domain-containing protein GIPC1 in diabetes is supported despite the lack of this information in the Online Mendelian Inheritance in Man database. Several key mediator proteins identified here clearly has pleiotropic effects, supported by ample evidence for their general but always of only secondary importance. CONCLUSIONS: We suggest that studying central nodes in mediator networks may contribute to better understanding and quantifying pleiotropy. Network analysis provides potentially useful tools here, as well as helps in improving databases. |
format | Online Article Text |
id | pubmed-3231966 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32319662011-12-12 Inferring pleiotropy by network analysis: linked diseases in the human PPI network Nguyen, Thanh-Phuong Liu, Wei-chung Jordán, Ferenc BMC Syst Biol Research Article BACKGROUND: Earlier, we identified proteins connecting different disease proteins in the human protein-protein interaction network and quantified their mediator role. An analysis of the networks of these mediators shows that proteins connecting heart disease and diabetes largely overlap with the ones connecting heart disease and obesity. RESULTS: We quantified their overlap, and based on the identified topological patterns, we inferred the structural disease-relatedness of several proteins. Literature data provide a functional look of them, well supporting our findings. For example, the inferred structurally important role of the PDZ domain-containing protein GIPC1 in diabetes is supported despite the lack of this information in the Online Mendelian Inheritance in Man database. Several key mediator proteins identified here clearly has pleiotropic effects, supported by ample evidence for their general but always of only secondary importance. CONCLUSIONS: We suggest that studying central nodes in mediator networks may contribute to better understanding and quantifying pleiotropy. Network analysis provides potentially useful tools here, as well as helps in improving databases. BioMed Central 2011-10-31 /pmc/articles/PMC3231966/ /pubmed/22034985 http://dx.doi.org/10.1186/1752-0509-5-179 Text en Copyright ©2011 Nguyen 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 Nguyen, Thanh-Phuong Liu, Wei-chung Jordán, Ferenc Inferring pleiotropy by network analysis: linked diseases in the human PPI network |
title | Inferring pleiotropy by network analysis: linked diseases in the human PPI network |
title_full | Inferring pleiotropy by network analysis: linked diseases in the human PPI network |
title_fullStr | Inferring pleiotropy by network analysis: linked diseases in the human PPI network |
title_full_unstemmed | Inferring pleiotropy by network analysis: linked diseases in the human PPI network |
title_short | Inferring pleiotropy by network analysis: linked diseases in the human PPI network |
title_sort | inferring pleiotropy by network analysis: linked diseases in the human ppi network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231966/ https://www.ncbi.nlm.nih.gov/pubmed/22034985 http://dx.doi.org/10.1186/1752-0509-5-179 |
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