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Logic-Based Models for the Analysis of Cell Signaling Networks

[Image: see text] Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolec...

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Detalles Bibliográficos
Autores principales: Morris, Melody K., Saez-Rodriguez, Julio, Sorger, Peter K., Lauffenburger, Douglas A.
Formato: Texto
Lenguaje:English
Publicado: American Chemical Society 2010
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853906/
https://www.ncbi.nlm.nih.gov/pubmed/20225868
http://dx.doi.org/10.1021/bi902202q
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author Morris, Melody K.
Saez-Rodriguez, Julio
Sorger, Peter K.
Lauffenburger, Douglas A.
author_facet Morris, Melody K.
Saez-Rodriguez, Julio
Sorger, Peter K.
Lauffenburger, Douglas A.
author_sort Morris, Melody K.
collection PubMed
description [Image: see text] Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks.
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spelling pubmed-28539062010-04-13 Logic-Based Models for the Analysis of Cell Signaling Networks Morris, Melody K. Saez-Rodriguez, Julio Sorger, Peter K. Lauffenburger, Douglas A. Biochemistry [Image: see text] Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. American Chemical Society 2010-03-12 2010-04-20 /pmc/articles/PMC2853906/ /pubmed/20225868 http://dx.doi.org/10.1021/bi902202q Text en Copyright © 2010 American Chemical Society http://pubs.acs.org This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org.
spellingShingle Morris, Melody K.
Saez-Rodriguez, Julio
Sorger, Peter K.
Lauffenburger, Douglas A.
Logic-Based Models for the Analysis of Cell Signaling Networks
title Logic-Based Models for the Analysis of Cell Signaling Networks
title_full Logic-Based Models for the Analysis of Cell Signaling Networks
title_fullStr Logic-Based Models for the Analysis of Cell Signaling Networks
title_full_unstemmed Logic-Based Models for the Analysis of Cell Signaling Networks
title_short Logic-Based Models for the Analysis of Cell Signaling Networks
title_sort logic-based models for the analysis of cell signaling networks
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2853906/
https://www.ncbi.nlm.nih.gov/pubmed/20225868
http://dx.doi.org/10.1021/bi902202q
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