Computational models in plant-pathogen interactions

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Subtitle: the case of Phytophthora infestans
Author list: Pinzon A, Barreto E, Bernal A, Achenie L, Barrios AFG, Isea R, Restrepo S
Publisher: BMC (part of Springer Nature)
Publication year: 2009
Journal: Theoretical Biology and Medical Modelling (1742-4682)
Volume number: 6
Issue number: 24
Number of pages: 11
ISSN: 1742-4682
Languages: English-Great Britain (EN-GB)


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.


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Last updated on 2019-23-08 at 11:15