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Connectedness of PPI network neighborhoods identifies regulatory hub proteins.
Fox, Andrew D; Hescott, Benjamin J; Blumer, Anselm C; Slonim, Donna K.
Afiliação
  • Fox AD; Department of Computer Science, Tufts University, Medford, MA 02155, USA. fox.andrew.d@gmail.com
Bioinformatics ; 27(8): 1135-42, 2011 Apr 15.
Article em En | MEDLINE | ID: mdl-21367871
MOTIVATION: With the growing availability of high-throughput protein-protein interaction (PPI) data, it has become possible to consider how a protein's local or global network characteristics predict its function. RESULTS: We introduce a graph-theoretic approach that identifies key regulatory proteins in an organism by analyzing proteins' local PPI network structure. We apply the method to the yeast genome and describe several properties of the resulting set of regulatory hubs. Finally, we demonstrate how the identified hubs and putative target gene sets can be used to identify causative, functional regulators of differential gene expression linked to human disease. AVAILABILITY: Code is available at http://bcb.cs.tufts.edu/hubcomps. CONTACT: fox.andrew.d@gmail.com; slonim@cs.tufts.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mapeamento de Interação de Proteínas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2011 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mapeamento de Interação de Proteínas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2011 Tipo de documento: Article País de afiliação: Estados Unidos