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Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis
Our method concentrates on and constructs the distinguished single gene network. An integrated method was proposed based on linear programming and a decomposition procedure with integrated analysis of the significant function cluster using Kappa statistics and fuzzy heuristic clustering. We tested t...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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Hindawi Publishing Corporation
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2668912/ https://www.ncbi.nlm.nih.gov/pubmed/19390583 http://dx.doi.org/10.1155/2009/726728 |
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author | Wang, Lin Sun, Ying Jiang, Minghu Zheng, Xiguang |
author_facet | Wang, Lin Sun, Ying Jiang, Minghu Zheng, Xiguang |
author_sort | Wang, Lin |
collection | PubMed |
description | Our method concentrates on and constructs the distinguished single gene network. An integrated method was proposed based on linear programming and a decomposition procedure with integrated analysis of the significant function cluster using Kappa statistics and fuzzy heuristic clustering. We tested this method to identify ATF2 regulatory network module using data of 45 samples from the same GEO dataset. The results demonstrate the effectiveness of such integrated way in terms of developing novel prognostic markers and therapeutic targets. |
format | Text |
id | pubmed-2668912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-26689122009-04-22 Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis Wang, Lin Sun, Ying Jiang, Minghu Zheng, Xiguang J Biomed Biotechnol Research Article Our method concentrates on and constructs the distinguished single gene network. An integrated method was proposed based on linear programming and a decomposition procedure with integrated analysis of the significant function cluster using Kappa statistics and fuzzy heuristic clustering. We tested this method to identify ATF2 regulatory network module using data of 45 samples from the same GEO dataset. The results demonstrate the effectiveness of such integrated way in terms of developing novel prognostic markers and therapeutic targets. Hindawi Publishing Corporation 2009 2009-04-14 /pmc/articles/PMC2668912/ /pubmed/19390583 http://dx.doi.org/10.1155/2009/726728 Text en Copyright © 2009 Lin Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wang, Lin Sun, Ying Jiang, Minghu Zheng, Xiguang Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis |
title | Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis |
title_full | Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis |
title_fullStr | Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis |
title_full_unstemmed | Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis |
title_short | Integrative Decomposition Procedure and Kappa Statistics for the Distinguished Single Molecular Network Construction and Analysis |
title_sort | integrative decomposition procedure and kappa statistics for the distinguished single molecular network construction and analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2668912/ https://www.ncbi.nlm.nih.gov/pubmed/19390583 http://dx.doi.org/10.1155/2009/726728 |
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