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Data and programs in support of network analysis of genes and their association with diseases
The network-based approaches that were employed in order to depict the relationships between human genetic diseases and their associated genes are described. Towards this direction, monopartite disease-disease and gene-gene networks were constructed from bipartite gene-disease association networks....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4969244/ https://www.ncbi.nlm.nih.gov/pubmed/27508260 http://dx.doi.org/10.1016/j.dib.2016.07.022 |
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author | Kontou, Panagiota I. Pavlopoulou, Athanasia Dimou, Niki L. Pavlopoulos, Georgios A. Bagos, Pantelis G. |
author_facet | Kontou, Panagiota I. Pavlopoulou, Athanasia Dimou, Niki L. Pavlopoulos, Georgios A. Bagos, Pantelis G. |
author_sort | Kontou, Panagiota I. |
collection | PubMed |
description | The network-based approaches that were employed in order to depict the relationships between human genetic diseases and their associated genes are described. Towards this direction, monopartite disease-disease and gene-gene networks were constructed from bipartite gene-disease association networks. The latter were created by collecting and integrating data from three diverse resources, each one with different content, covering from rare monogenic disorders to common complex diseases. Moreover, topological and clustering graph analyses were performed. The methodology and the programs presented in this article are related to the research article entitled “Network analysis of genes and their association with diseases” [1]. |
format | Online Article Text |
id | pubmed-4969244 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-49692442016-08-09 Data and programs in support of network analysis of genes and their association with diseases Kontou, Panagiota I. Pavlopoulou, Athanasia Dimou, Niki L. Pavlopoulos, Georgios A. Bagos, Pantelis G. Data Brief Data Article The network-based approaches that were employed in order to depict the relationships between human genetic diseases and their associated genes are described. Towards this direction, monopartite disease-disease and gene-gene networks were constructed from bipartite gene-disease association networks. The latter were created by collecting and integrating data from three diverse resources, each one with different content, covering from rare monogenic disorders to common complex diseases. Moreover, topological and clustering graph analyses were performed. The methodology and the programs presented in this article are related to the research article entitled “Network analysis of genes and their association with diseases” [1]. Elsevier 2016-07-19 /pmc/articles/PMC4969244/ /pubmed/27508260 http://dx.doi.org/10.1016/j.dib.2016.07.022 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Kontou, Panagiota I. Pavlopoulou, Athanasia Dimou, Niki L. Pavlopoulos, Georgios A. Bagos, Pantelis G. Data and programs in support of network analysis of genes and their association with diseases |
title | Data and programs in support of network analysis of genes and their association with diseases |
title_full | Data and programs in support of network analysis of genes and their association with diseases |
title_fullStr | Data and programs in support of network analysis of genes and their association with diseases |
title_full_unstemmed | Data and programs in support of network analysis of genes and their association with diseases |
title_short | Data and programs in support of network analysis of genes and their association with diseases |
title_sort | data and programs in support of network analysis of genes and their association with diseases |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4969244/ https://www.ncbi.nlm.nih.gov/pubmed/27508260 http://dx.doi.org/10.1016/j.dib.2016.07.022 |
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