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Logic Modeling in Quantitative Systems Pharmacology

Here we present logic modeling as an approach to understand deregulation of signal transduction in disease and to characterize a drug's mode of action. We discuss how to build a logic model from the literature and experimental data and how to analyze the resulting model to obtain insights of re...

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Detalles Bibliográficos
Autores principales: Traynard, Pauline, Tobalina, Luis, Eduati, Federica, Calzone, Laurence, Saez‐Rodriguez, Julio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572374/
https://www.ncbi.nlm.nih.gov/pubmed/28681552
http://dx.doi.org/10.1002/psp4.12225
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author Traynard, Pauline
Tobalina, Luis
Eduati, Federica
Calzone, Laurence
Saez‐Rodriguez, Julio
author_facet Traynard, Pauline
Tobalina, Luis
Eduati, Federica
Calzone, Laurence
Saez‐Rodriguez, Julio
author_sort Traynard, Pauline
collection PubMed
description Here we present logic modeling as an approach to understand deregulation of signal transduction in disease and to characterize a drug's mode of action. We discuss how to build a logic model from the literature and experimental data and how to analyze the resulting model to obtain insights of relevance for systems pharmacology. Our workflow uses the free tools OmniPath (network reconstruction from the literature), CellNOpt (model fit to experimental data), MaBoSS (model analysis), and Cytoscape (visualization).
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spelling pubmed-55723742017-08-30 Logic Modeling in Quantitative Systems Pharmacology Traynard, Pauline Tobalina, Luis Eduati, Federica Calzone, Laurence Saez‐Rodriguez, Julio CPT Pharmacometrics Syst Pharmacol Tutorial Here we present logic modeling as an approach to understand deregulation of signal transduction in disease and to characterize a drug's mode of action. We discuss how to build a logic model from the literature and experimental data and how to analyze the resulting model to obtain insights of relevance for systems pharmacology. Our workflow uses the free tools OmniPath (network reconstruction from the literature), CellNOpt (model fit to experimental data), MaBoSS (model analysis), and Cytoscape (visualization). John Wiley and Sons Inc. 2017-07-29 2017-08 /pmc/articles/PMC5572374/ /pubmed/28681552 http://dx.doi.org/10.1002/psp4.12225 Text en © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial (http://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Tutorial
Traynard, Pauline
Tobalina, Luis
Eduati, Federica
Calzone, Laurence
Saez‐Rodriguez, Julio
Logic Modeling in Quantitative Systems Pharmacology
title Logic Modeling in Quantitative Systems Pharmacology
title_full Logic Modeling in Quantitative Systems Pharmacology
title_fullStr Logic Modeling in Quantitative Systems Pharmacology
title_full_unstemmed Logic Modeling in Quantitative Systems Pharmacology
title_short Logic Modeling in Quantitative Systems Pharmacology
title_sort logic modeling in quantitative systems pharmacology
topic Tutorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572374/
https://www.ncbi.nlm.nih.gov/pubmed/28681552
http://dx.doi.org/10.1002/psp4.12225
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