Your browser doesn't support javascript.
loading
Protein Subcellular Localization Prediction.
Barberis, Elettra; Marengo, Emilio; Manfredi, Marcello.
Afiliação
  • Barberis E; Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
  • Marengo E; Center for Translational Research on Autoimmune and Allergic Diseases, CAAD, University of Piemonte Orientale, Novara, Italy.
  • Manfredi M; Department of Sciences and Technological Innovation, University of Piemonte Orientale, Alessandria, Italy.
Methods Mol Biol ; 2361: 197-212, 2021.
Article em En | MEDLINE | ID: mdl-34236663
ABSTRACT
The elucidation of the subcellular localization of proteins is very important in order to deeply understand their functions. In fact, proteins activities are strictly correlated to the cellular compartment and microenvironment in which they are present.In recent years, several effective and reliable proteomics techniques and computational methods have been developed and implemented in order to identify the proteins subcellular localization. This process is often time-consuming and expensive, but the recent technological and bioinformatics progress allowed the development of more accurate and simple workflows to determine the localization, interactions, and functions of proteins.In the following chapter, a brief introduction on the importance of knowing subcellular localization of proteins will be presented. Then, sample preparation protocols, proteomic methods, data analysis strategies, and software for the prediction of proteins localization will be presented and discussed. Finally, the more recent and advanced spatial proteomics techniques will be shown.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteômica Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Methods Mol Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteômica Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Methods Mol Biol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Itália