Your browser doesn't support javascript.
loading
Rough hypercuboid based supervised clustering of miRNAs.
Paul, Sushmita; Vera, Julio.
Afiliação
  • Paul S; Laboratory of Systems Tumor Immunology, Department of Dermatology, University of Erlangen-Nürnberg, Hartmannstr. 14, 91052 Erlangen, Germany. sushmita.paul@uk-erlangen.de julio.vera-gonzalez@uk-erlangen.de.
Mol Biosyst ; 11(7): 2068-81, 2015 Jul.
Article em En | MEDLINE | ID: mdl-25996345
The microRNAs are small, endogenous non-coding RNAs found in plants, animals, and some viruses, which function in RNA silencing and post-transcriptional regulation of gene expression. It is suggested by various genome-wide studies that a substantial fraction of miRNA genes is likely to form clusters. The coherent expression of the miRNA clusters can then be used to classify samples according to the clinical outcome. In this regard, a new clustering algorithm, termed as rough hypercuboid based supervised attribute clustering (RH-SAC), is proposed to find such groups of miRNAs. The proposed algorithm is based on the theory of rough set, which directly incorporates the information of sample categories into the miRNA clustering process, generating a supervised clustering algorithm for miRNAs. The effectiveness of the new approach is demonstrated on several publicly available miRNA expression data sets using support vector machine. The so-called B.632+ bootstrap error estimate is used to minimize the variability and biasedness of the derived results. The association of the miRNA clusters to various biological pathways is also shown by doing pathway enrichment analysis.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: MicroRNAs Limite: Humans Idioma: En Revista: Mol Biosyst Assunto da revista: BIOLOGIA MOLECULAR / BIOQUIMICA Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: MicroRNAs Limite: Humans Idioma: En Revista: Mol Biosyst Assunto da revista: BIOLOGIA MOLECULAR / BIOQUIMICA Ano de publicação: 2015 Tipo de documento: Article