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Título: Biclustering Algorithm for Embryonic Tumor Gene Expression Dataset: LAS Algorithm
Autores: Alavi Majd, Hamid; Biostatistics Department, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran
Shahsavari, Soodeh; Biostatistics Department, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran
Khodakarim, Soheila; School of Public Health, Shahid Beheshti University of Medical Science, Tehran
Tabatabaei, Seyyed Mohammad; Medical Informatics Department, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran
Nobakht Motlagh Ghochani, Bi bi Fatemeh; Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran
Fecha: 2013-03-02
Publicador: Journal of Paramedical Sciences
Fuente: Ver documento
Tipo: info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion


Tema: Biclustering algorithm; LAS procedure; Gene expression data
Biclustering Algorithm for Embryonic Tumor Gene Expression Dataset: LAS Algorithm
Descripción: An important step in considering of gene expression data is obtained groups of genes that have similarity patterns. Biclustering methods was recently introduced for discovering subsets of genes that have coherent values across a subset of conditions. The LAS algorithm relies on a heuristic randomized search to find biclusters. In this paper, we introduce biclustering LAS algorithm and then apply this procedure for real value gene expression data. In this study after normalized data, LAS performed. 31 biclusters were  discovered that 26 of them were for positive gene expression values and others were for negative. Biological validity for LAS procedure in biological process, in molecular function and in cellular component were 77.96% , 62.28% and 74.39% respictively. The result of biological validation of LAS algorithm in this study had shown LAS algorithm effectively convenient in discovering good biclusters.
Idioma: Inglés
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