ReviewTheoretical biology & medical modelling2009
Computational models in plant-pathogen interactions: the case of Phytophthora infestans.
Review in Theoretical biology & medical modelling, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Plant Biotic Stress: Tools and Techniques for Crop Protection.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Unravelling Plant Responses to Stress-The Importance of Targeted and Untargeted Metabolomics.Metabolites · 2021Review
- Uncovering the Role of Metabolism in Oomycete-Host Interactions Using Genome-Scale Metabolic Models.Frontiers in microbiology · 2021Review
- Metabolomics to Exploit the Primed Immune System of Tomato Fruit.Metabolites · 2020Article
- A genome-scale metabolic model of potato late blight suggests a photosynthesis suppression mechanism.BMC genomics · 2018Article
- Modeling the spread of Phytophthora.Journal of mathematical biology · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPhytophthora 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
conclusionDeterministic 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.