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Statistical analysis of molecule colocalization in bioimaging.
Lagache, Thibault; Sauvonnet, Nathalie; Danglot, Lydia; Olivo-Marin, Jean-Christophe.
Afiliação
  • Lagache T; Cell Biology and Infection Department, BioImage Analysis Unit, Institut Pasteur, 75724 Paris Cedex 15, France.
  • Sauvonnet N; Cell Biology and Infection Department, Molecular Microbial Pathogenesis Unit, Institut Pasteur, 75724 Paris Cedex 15, France.
  • Danglot L; Membrane Traffic in Heath and Disease Unit - Inserm 950. Institut Jacques Monod - CNRS UMR7592, Université Paris Diderot, 75205 Paris Cedex 13, France.
  • Olivo-Marin JC; Cell Biology and Infection Department, BioImage Analysis Unit, Institut Pasteur, 75724 Paris Cedex 15, France.
Cytometry A ; 87(6): 568-79, 2015 Jun.
Article em En | MEDLINE | ID: mdl-25605428
The quantitative analysis of molecule interactions in bioimaging is key for understanding the molecular orchestration of cellular processes and is generally achieved through the study of the spatial colocalization between the different populations of molecules. Colocalization methods are traditionally divided into pixel-based methods that measure global correlation coefficients from the overlap between pixel intensities in different color channels, and object-based methods that first segment molecule spots and then analyze their spatial distributions with second-order statistics. Here, we present a review of such colocalization methods and give a quantitative comparison of their relative merits in different types of biological applications and contexts. We show on synthetic and biological images that object-based methods are more robust statistically than pixel-based methods, and allow moreover to quantify accurately the number of colocalized molecules.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Interpretação de Imagem Assistida por Computador / Biologia Computacional Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Interpretação de Imagem Assistida por Computador / Biologia Computacional Idioma: En Ano de publicação: 2015 Tipo de documento: Article