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Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks
The gene interaction network is one of the most important biological networks and has been studied by many researchers. The gene interaction network provides information about whether the genes in the network can cause or heal diseases. As gene-gene interaction relations are constantly explored, gen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428845/ https://www.ncbi.nlm.nih.gov/pubmed/30899072 http://dx.doi.org/10.1038/s41598-019-41539-w |
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author | Yin, Ziqiao Guo, Binghui Mi, Zhilong Li, Jiahui Zheng, Zhiming |
author_facet | Yin, Ziqiao Guo, Binghui Mi, Zhilong Li, Jiahui Zheng, Zhiming |
author_sort | Yin, Ziqiao |
collection | PubMed |
description | The gene interaction network is one of the most important biological networks and has been studied by many researchers. The gene interaction network provides information about whether the genes in the network can cause or heal diseases. As gene-gene interaction relations are constantly explored, gene interaction networks are evolving. To describe how much a gene has been studied, an approach based on a logistic model for each gene called gene saturation has been proposed, which in most cases, satisfies non-decreasing, correlation and robustness principles. The average saturation of a group of genes can be used to assess the network constructed by these genes. Saturation reflects the distance between known gene interaction networks and the real gene interaction network in a cell. Furthermore, the saturation values of 546 disease gene networks that belong to 15 categories of diseases have been calculated. The disease gene networks’ saturation for cancer is significantly higher than that of all other diseases, which means that the disease gene networks’ structure for cancer has been more deeply studied than other disease. Gene saturation provides guidance for selecting an experimental subject gene, which may have a large number of unknown interactions. |
format | Online Article Text |
id | pubmed-6428845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64288452019-03-28 Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks Yin, Ziqiao Guo, Binghui Mi, Zhilong Li, Jiahui Zheng, Zhiming Sci Rep Article The gene interaction network is one of the most important biological networks and has been studied by many researchers. The gene interaction network provides information about whether the genes in the network can cause or heal diseases. As gene-gene interaction relations are constantly explored, gene interaction networks are evolving. To describe how much a gene has been studied, an approach based on a logistic model for each gene called gene saturation has been proposed, which in most cases, satisfies non-decreasing, correlation and robustness principles. The average saturation of a group of genes can be used to assess the network constructed by these genes. Saturation reflects the distance between known gene interaction networks and the real gene interaction network in a cell. Furthermore, the saturation values of 546 disease gene networks that belong to 15 categories of diseases have been calculated. The disease gene networks’ saturation for cancer is significantly higher than that of all other diseases, which means that the disease gene networks’ structure for cancer has been more deeply studied than other disease. Gene saturation provides guidance for selecting an experimental subject gene, which may have a large number of unknown interactions. Nature Publishing Group UK 2019-03-21 /pmc/articles/PMC6428845/ /pubmed/30899072 http://dx.doi.org/10.1038/s41598-019-41539-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Yin, Ziqiao Guo, Binghui Mi, Zhilong Li, Jiahui Zheng, Zhiming Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks |
title | Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks |
title_full | Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks |
title_fullStr | Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks |
title_full_unstemmed | Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks |
title_short | Gene Saturation: An Approach to Assess Exploration Stage of Gene Interaction Networks |
title_sort | gene saturation: an approach to assess exploration stage of gene interaction networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428845/ https://www.ncbi.nlm.nih.gov/pubmed/30899072 http://dx.doi.org/10.1038/s41598-019-41539-w |
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