title: Computational modeling of heterogeneity and function of CD4+ T cells.
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.
authors.affiliation: 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.
authors.forename: Adria
authors.initials: A
authors.lastname: Carbo
authors.affiliation: 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.
authors.forename: Raquel
authors.initials: R
authors.lastname: Hontecillas
authors.affiliation: 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.
authors.forename: Tricity
authors.initials: T
authors.lastname: Andrew
authors.affiliation: 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.
authors.forename: Kristin
authors.initials: K
authors.lastname: Eden
authors.affiliation: 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.
authors.forename: Yongguo
authors.initials: Y
authors.lastname: Mei
authors.affiliation: Center for Modeling Immunity to Enteric Pathogens, Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA, USA.
authors.forename: Stefan
authors.initials: S
authors.lastname: Hoops
authors.affiliation: 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 Pathobiology, Virginia-Maryland Regional College of Veterinary Medicine, Virginia Tech Blacksburg, VA, USA.
authors.forename: Josep
authors.initials: J
authors.lastname: Bassaganya-Riera
keywords: CD4+ T cell differentiation; CD4+ T cell dogma; computational immunology; computational modeling; immunoinformatics