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Computational models in plant-pathogen interactions: the case of Phytophthora infestans
- Source :
- Theoretical Biology & Medical Modelling, Theoretical Biology and Medical Modelling, Vol 6, Iss 1, p 24 (2009)
- Publication Year :
- 2009
-
Abstract
- 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.
- Subjects :
- Stochastic modelling
Phytophthora infestans
Systems biology
Health Informatics
Computational biology
Review
lcsh:Computer applications to medicine. Medical informatics
Modelling and Simulation
Protein Interaction Mapping
lcsh:QH301-705.5
Plant Diseases
Solanum tuberosum
Comparative genomics
Oomycete
Computational model
Biological data
Stochastic Processes
biology
business.industry
Gene Expression Profiling
food and beverages
Computational Biology
Genomics
Models, Theoretical
biology.organism_classification
Biotechnology
Kinetics
lcsh:Biology (General)
Gene Expression Regulation
Modeling and Simulation
lcsh:R858-859.7
business
Software
Signal Transduction
Subjects
Details
- ISSN :
- 17424682
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- Theoretical biologymedical modelling
- Accession number :
- edsair.doi.dedup.....365e69109acd893df1ed8af6e5356f7e