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Computational modeling of heterogeneity and function of CD4+ T cells.
Carbo, Adria; Hontecillas, Raquel; Andrew, Tricity; Eden, Kristin; Mei, Yongguo; Hoops, Stefan; Bassaganya-Riera, Josep.
Afiliação
  • Carbo A; Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA ; Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA.
  • Hontecillas R; Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA ; Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA.
  • Andrew T; Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA ; Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA.
  • Eden K; Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA ; Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA.
  • Mei Y; Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA ; Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA.
  • Hoops S; Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA.
  • Bassaganya-Riera J; Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA ; Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA ; Department of Biomedical Sciences and Pathobiolog
Front Cell Dev Biol ; 2: 31, 2014.
Article em En | MEDLINE | ID: mdl-25364738
ABSTRACT
The immune system is composed of many different cell types and hundreds of intersecting molecular pathways and signals. This large biological complexity requires coordination between distinct pro-inflammatory and regulatory cell subsets to respond to infection while maintaining tissue homeostasis. CD4+ T cells play a central role in orchestrating immune responses and in maintaining a balance between pro- and anti- inflammatory responses. This tight balance between regulatory and effector reactions depends on the ability of CD4+ T cells to modulate distinct pathways within large molecular networks, since dysregulated CD4+ T cell responses may result in chronic inflammatory and autoimmune diseases. The CD4+ T cell differentiation process comprises an intricate interplay between cytokines, their receptors, adaptor molecules, signaling cascades and transcription factors that help delineate cell fate and function. Computational modeling can help to describe, simulate, analyze, and predict some of the behaviors in this complicated differentiation network. This review provides a comprehensive overview of existing computational immunology methods as well as novel strategies used to model immune responses with a particular focus on CD4+ T cell differentiation.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Cell Dev Biol Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Cell Dev Biol Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Estados Unidos