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An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis

Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in t...

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Detalles Bibliográficos
Autores principales: Qu, Hua, Wang, Liu-Pu, Liang, Yan-Chun, Wu, Chun-Guo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5172552/
https://www.ncbi.nlm.nih.gov/pubmed/16487084
http://dx.doi.org/10.1016/S1672-0229(05)03024-X
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author Qu, Hua
Wang, Liu-Pu
Liang, Yan-Chun
Wu, Chun-Guo
author_facet Qu, Hua
Wang, Liu-Pu
Liang, Yan-Chun
Wu, Chun-Guo
author_sort Qu, Hua
collection PubMed
description Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition while the computational time does not increase significantly.
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spelling pubmed-51725522016-12-23 An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis Qu, Hua Wang, Liu-Pu Liang, Yan-Chun Wu, Chun-Guo Genomics Proteomics Bioinformatics Method Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition while the computational time does not increase significantly. Elsevier 2005 2016-11-28 /pmc/articles/PMC5172552/ /pubmed/16487084 http://dx.doi.org/10.1016/S1672-0229(05)03024-X Text en . http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Method
Qu, Hua
Wang, Liu-Pu
Liang, Yan-Chun
Wu, Chun-Guo
An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis
title An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis
title_full An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis
title_fullStr An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis
title_full_unstemmed An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis
title_short An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis
title_sort improved biclustering algorithm and its application to gene expression spectrum analysis
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5172552/
https://www.ncbi.nlm.nih.gov/pubmed/16487084
http://dx.doi.org/10.1016/S1672-0229(05)03024-X
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