Abstract
In order to increase our understanding of biological dependencies in plant immune signaling pathways, the known interactions involved in plant immune networks are modeled. This allows computational analysis to predict the functions of growth related hormones in plant–pathogen interaction. The SQUAD (Standardized Qualitative Dynamical Systems) algorithm first determines stable system states in the network and then use them to compute continuous dynamical system states. Our reconstructed Boolean model encompassing hormone immune networks of Arabidopsis thaliana (Arabidopsis) and pathogenicity factors injected by model pathogen Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) can be exploited to determine the impact of growth hormones in plant immunity. We describe a detailed working protocol how to use the modified SQUAD-package by exemplifying the contrasting effects of auxin and cytokinins in shaping plant–pathogen interaction.
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We thank the German Research Foundation (DFG) for funding (TR124/B1)
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Kaltdorf, M., Dandekar, T., Naseem, M. (2017). Reconstruction of an Immune Dynamic Model to Simulate the Contrasting Role of Auxin and Cytokinin in Plant Immunity. In: Dandekar, T., Naseem, M. (eds) Auxins and Cytokinins in Plant Biology. Methods in Molecular Biology, vol 1569. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6831-2_6
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DOI: https://doi.org/10.1007/978-1-4939-6831-2_6
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