Literature DB >> 17367343

Computer immunology.

Stephanie Forrest1, Catherine Beauchemin.   

Abstract

This review describes a body of work on computational immune systems that behave analogously to the natural immune system. These artificial immune systems (AIS) simulate the behavior of the natural immune system and in some cases have been used to solve practical engineering problems such as computer security. AIS have several strengths that can complement wet lab immunology. It is easier to conduct simulation experiments and to vary experimental conditions, for example, to rule out hypotheses; it is easier to isolate a single mechanism to test hypotheses about how it functions; agent-based models of the immune system can integrate data from several different experiments into a single in silico experimental system.

Mesh:

Year:  2007        PMID: 17367343     DOI: 10.1111/j.1600-065X.2007.00499.x

Source DB:  PubMed          Journal:  Immunol Rev        ISSN: 0105-2896            Impact factor:   12.988


  19 in total

Review 1.  Systems immunology: a survey of modeling formalisms, applications and simulation tools.

Authors:  Vipin Narang; James Decraene; Shek-Yoon Wong; Bindu S Aiswarya; Andrew R Wasem; Shiang Rong Leong; Alexandre Gouaillard
Journal:  Immunol Res       Date:  2012-09       Impact factor: 2.829

2.  Maximal frustration as an immunological principle.

Authors:  F Vistulo de Abreu; P Mostardinha
Journal:  J R Soc Interface       Date:  2009-03-06       Impact factor: 4.118

Review 3.  Synthetic transitions: towards a new synthesis.

Authors:  Ricard Solé
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-08-19       Impact factor: 6.237

4.  The major synthetic evolutionary transitions.

Authors:  Ricard Solé
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-08-19       Impact factor: 6.237

Review 5.  Solving Immunology?

Authors:  Yoram Vodovotz; Ashley Xia; Elizabeth L Read; Josep Bassaganya-Riera; David A Hafler; Eduardo Sontag; Jin Wang; John S Tsang; Judy D Day; Steven H Kleinstein; Atul J Butte; Matthew C Altman; Ross Hammond; Stuart C Sealfon
Journal:  Trends Immunol       Date:  2016-12-13       Impact factor: 16.687

6.  Parameter estimation and sensitivity analysis in an agent-based model of Leishmania major infection.

Authors:  Garrett M Dancik; Douglas E Jones; Karin S Dorman
Journal:  J Theor Biol       Date:  2009-10-23       Impact factor: 2.691

7.  Agent-based modeling of host-pathogen systems: The successes and challenges.

Authors:  Amy L Bauer; Catherine A A Beauchemin; Alan S Perelson
Journal:  Inf Sci (N Y)       Date:  2009-04-29       Impact factor: 6.795

8.  Agent-based modeling approach of immune defense against spores of opportunistic human pathogenic fungi.

Authors:  Christian Tokarski; Sabine Hummert; Franziska Mech; Marc Thilo Figge; Sebastian Germerodt; Anja Schroeter; Stefan Schuster
Journal:  Front Microbiol       Date:  2012-04-26       Impact factor: 5.640

9.  Pairing experimentation and computational modeling to understand the role of tissue inducer cells in the development of lymphoid organs.

Authors:  Kieran Alden; Jon Timmis; Paul S Andrews; Henrique Veiga-Fernandes; Mark C Coles
Journal:  Front Immunol       Date:  2012-07-18       Impact factor: 7.561

10.  Positive and negative selection, self-nonself discrimination and the roles of costimulation and anergy.

Authors:  P Mostardinha; F Vistulo de Abreu
Journal:  Sci Rep       Date:  2012-10-25       Impact factor: 4.379

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