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Provedor de dados:  Genet. Mol. Biol.
País:  Brazil
Título:  Combination of meta-analysis and graph clustering to identify prognostic markers of ESCC
Autores:  Gao,Hongyun
Data:  2012-01-01
Ano:  2012
Palavras-chave:  Esophageal squamous cell carcinoma
Graph clustering
Resumo:  Esophageal squamous cell carcinoma (ESCC) is one of the most malignant gastrointestinal cancers and occurs at a high frequency rate in China and other Asian countries. Recently, several molecular markers were identified for predicting ESCC. Notwithstanding, additional prognostic markers, with a clear understanding of their underlying roles, are still required. Through bioinformatics, a graph-clustering method by DPClus was used to detect co-expressed modules. The aim was to identify a set of discriminating genes that could be used for predicting ESCC through graph-clustering and GO-term analysis. The results showed that CXCL12, CYP2C9, TGM3, MAL, S100A9, EMP-1 and SPRR3 were highly associated with ESCC development. In our study, all their predicted roles were in line with previous reports, whereby the assumption that a combination of meta-analysis, graph-clustering and GO-term analysis is effective for both identifying differentially expressed genes, and reflecting on their functions in ESCC.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Editor:  Sociedade Brasileira de Genética
Relação:  10.1590/S1415-47572012000300021
Formato:  text/html
Fonte:  Genetics and Molecular Biology v.35 n.2 2012
Direitos:  info:eu-repo/semantics/openAccess

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