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Computational models in plant-pathogen interactions: the case of Phytophthora infestans
BACKGROUND: Phytophthora infestans is a devastating oomycete pathogen of potato production worldwide. This review explores the use of computational models for studying the molecular interactions between P. infestans and one of its hosts, Solanum tuberosum. MODELING AND CONCLUSION: Deterministic logi...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2787490/ https://www.ncbi.nlm.nih.gov/pubmed/19909526 http://dx.doi.org/10.1186/1742-4682-6-24 |
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author | Pinzón, Andrés Barreto, Emiliano Bernal, Adriana Achenie, Luke González Barrios, Andres F Isea, Raúl Restrepo, Silvia |
author_facet | Pinzón, Andrés Barreto, Emiliano Bernal, Adriana Achenie, Luke González Barrios, Andres F Isea, Raúl Restrepo, Silvia |
author_sort | Pinzón, Andrés |
collection | PubMed |
description | BACKGROUND: Phytophthora infestans is a devastating oomycete pathogen of potato production worldwide. This review explores the use of computational models for studying the molecular interactions between P. infestans and one of its hosts, Solanum tuberosum. MODELING AND CONCLUSION: Deterministic logistics models have been widely used to study pathogenicity mechanisms since the early 1950s, and have focused on processes at higher biological resolution levels. In recent years, owing to the availability of high throughput biological data and computational resources, interest in stochastic modeling of plant-pathogen interactions has grown. Stochastic models better reflect the behavior of biological systems. Most modern approaches to plant pathology modeling require molecular kinetics information. Unfortunately, this information is not available for many plant pathogens, including P. infestans. Boolean formalism has compensated for the lack of kinetics; this is especially the case where comparative genomics, protein-protein interactions and differential gene expression are the most common data resources. |
format | Text |
id | pubmed-2787490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27874902009-12-03 Computational models in plant-pathogen interactions: the case of Phytophthora infestans Pinzón, Andrés Barreto, Emiliano Bernal, Adriana Achenie, Luke González Barrios, Andres F Isea, Raúl Restrepo, Silvia Theor Biol Med Model Review BACKGROUND: Phytophthora infestans is a devastating oomycete pathogen of potato production worldwide. This review explores the use of computational models for studying the molecular interactions between P. infestans and one of its hosts, Solanum tuberosum. MODELING AND CONCLUSION: Deterministic logistics models have been widely used to study pathogenicity mechanisms since the early 1950s, and have focused on processes at higher biological resolution levels. In recent years, owing to the availability of high throughput biological data and computational resources, interest in stochastic modeling of plant-pathogen interactions has grown. Stochastic models better reflect the behavior of biological systems. Most modern approaches to plant pathology modeling require molecular kinetics information. Unfortunately, this information is not available for many plant pathogens, including P. infestans. Boolean formalism has compensated for the lack of kinetics; this is especially the case where comparative genomics, protein-protein interactions and differential gene expression are the most common data resources. BioMed Central 2009-11-12 /pmc/articles/PMC2787490/ /pubmed/19909526 http://dx.doi.org/10.1186/1742-4682-6-24 Text en Copyright ©2009 Pinzón et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Pinzón, Andrés Barreto, Emiliano Bernal, Adriana Achenie, Luke González Barrios, Andres F Isea, Raúl Restrepo, Silvia Computational models in plant-pathogen interactions: the case of Phytophthora infestans |
title | Computational models in plant-pathogen interactions: the case of Phytophthora infestans |
title_full | Computational models in plant-pathogen interactions: the case of Phytophthora infestans |
title_fullStr | Computational models in plant-pathogen interactions: the case of Phytophthora infestans |
title_full_unstemmed | Computational models in plant-pathogen interactions: the case of Phytophthora infestans |
title_short | Computational models in plant-pathogen interactions: the case of Phytophthora infestans |
title_sort | computational models in plant-pathogen interactions: the case of phytophthora infestans |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2787490/ https://www.ncbi.nlm.nih.gov/pubmed/19909526 http://dx.doi.org/10.1186/1742-4682-6-24 |
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