Data/hora: 13/06/2024 02:58:40

Provedor de dados: | 74
País: | Brazil
Título: | Combination of meta-analysis and graph clustering to identify prognostic markers of ESCC
Autores: | Gao,Hongyun; Wang,Lishan; Cui,Shitao; Wang,Mingsong.
Data: | 2012-01-01
Ano: | 2012
Palavras-chave: | Esophageal squamous cell carcinoma; Meta-analysis; 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
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572012000300021
Editor: | Sociedade Brasileira de Genética
Relação: | 10.1590/S1415-47572012000300021
Formato: | text/html
Fonte: | Genetics and Molecular Biology  v.35 n.2 2012
Fonte: | info:eu-repo/semantics/openAccess