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PSCL: predicting protein subcellular localization based on optimal functional domains.
Wang, Kai; Hu, Le-Le; Shi, Xiao-He; Dong, Ying-Song; Li, Hai-Peng; Wen, Tie-Qiao.
Afiliação
  • Wang K; Laboratory of Molecular Neurobiology, School of Life Sciences, Shanghai University, Shanghai, PR China.
Protein Pept Lett ; 19(1): 15-22, 2012 Jan.
Article em En | MEDLINE | ID: mdl-21919864
ABSTRACT
It is well known that protein subcellular localizations are closely related to their functions. Although many computational methods and tools are available from Internet, it is still necessary to develop new algorithms in this filed to gain a better understanding of the complex mechanism of plant subcellular localization. Here, we provide a new web server named PSCL for plant protein subcellular localization prediction by employing optimized functional domains. After feature optimization, 848 optimal functional domains from InterPro were obtained to represent each protein. By calculating the distances to each of the seven categories, PSCL showing the possibilities of a protein located into each of those categories in ascending order. Toward our dataset, PSCL achieved a first-order predicted accuracy of 75.7% by jackknife test. Gene Ontology enrichment analysis showing that catalytic activity, cellular process and metabolic process are strongly correlated with the localization of plant proteins. Finally, PSCL, a Linux Operate System based web interface for the predictor was designed and is accessible for public use at http//pscl.biosino.org/.
Assuntos
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas de Plantas / Plantas / Frações Subcelulares / Software / Células Vegetais Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Protein Pept Lett Ano de publicação: 2012 Tipo de documento: Article
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas de Plantas / Plantas / Frações Subcelulares / Software / Células Vegetais Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Protein Pept Lett Ano de publicação: 2012 Tipo de documento: Article