Your browser doesn't support javascript.
loading
From promoter analysis to transcriptional regulatory network prediction using PAINT.
Gonye, Gregory E; Chakravarthula, Praveen; Schwaber, James S; Vadigepalli, Rajanikanth.
Afiliação
  • Gonye GE; Thomas Jefferson University, Philadelphia, PA, USA.
Methods Mol Biol ; 408: 49-68, 2007.
Article em En | MEDLINE | ID: mdl-18314577
ABSTRACT
Highly parallel gene-expression analysis has led to analysis of gene regulation, in particular coregulation, at a system level. Promoter analysis and interaction network toolset (PAINT) was developed to provide the biologist a computational tool to integrate functional genomics data, for example, from microarray-based gene-expression analysis with genomic sequence data to carry out transcriptional regulatory network analysis (TRNA). TRNA combines bioinformatics, used to identify and analyze gene-regulatory regions, and statistical significance testing, used to rank the likelihood of the involvement of individual transcription factors (TF), with visualization tools to identify TF likely to play a role in the cellular process under investigation. In summary, given a list of gene identifiers PAINT can (1) fetch potential promoter sequences for the genes in the list, (2) find TF-binding sites on the sequences, (3) analyze the TF-binding site occurrences for over/under-representation compared with a reference, with or without coexpression clustering information, and (4) generate multiple visualizations for these analyses. At present, PAINT supports TRNA of the human, mouse, and rat genomes. PAINT is currently available as an online, web-based service located at http//www.dbi.tju.edu/dbi/tools/paint.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Regiões Promotoras Genéticas / Perfilação da Expressão Gênica / Genômica Idioma: En Ano de publicação: 2007 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Regiões Promotoras Genéticas / Perfilação da Expressão Gênica / Genômica Idioma: En Ano de publicação: 2007 Tipo de documento: Article