Numeric Simulation of Plant Signaling Networks

• Published in: Plant physiology (Bethesda) Vol. 126; no. 4; pp. 1430 - 1437
• Main Authors: Genoud, Thierry, Marcela B. Trevino Santa Cruz, Métraux, Jean-Pierre
• Format: Journal Article
• Language: English
• Published: Rockville, MD American Society of Plant Biologists 01.08.2001; American Society of Plant Physiologists
• Subjects: Algorithms; Arabidopsis; Arabidopsis - genetics; biochemical pathways; Biological and medical sciences; Boolean data; Cell physiology; Computer Simulation; Crosstalk; defense mechanisms; Developmental stages; Disease resistance; Environmental conditions; Fundamental and applied biological sciences. Psychology; Gene expression; Gene expression regulation; Genes; genetics; Genetics, Genomics, and Molecular Evolution; Models, Biological; Molecular and cellular biology; Operating rooms; Pathogens; Plant cells; Plant Diseases; Programming Languages; Signal Transduction; simulation models; Computer simulation; Biological model; Environmental factor; Proteome; Review; Metabolism; Arabidopsis thaliana; Infection; Signal transduction; Cruciferae; Boolean logic; Dicotyledones; Angiospermae; Numerical simulation; Spermatophyta; Developmental stage; Experimental plant; Genome; Adaptation
• ISSN: 0032-0889; 1532-2548; 1532-2548
• DOI: 10.1104/pp.126.4.1430

Plants have evolved an intricate signaling apparatus that integrates relevant information and allows an optimal response to environmental conditions. For instance, the coordination of defense responses against pathogens involves sophisticated molecular detection and communication systems. Multiple protection strategies may be deployed differentially by the plant according to the nature of the invading organism. These responses are also influenced by the environment, metabolism, and developmental stage of the plant. Though the cellular signaling processes traditionally have been described as linear sequences of events, it is now evident that they may be represented more accurately as network-like structures. The emerging paradigm can be represented readily with the use of Boolean language. This digital (numeric) formalism allows an accurate qualitative description of the signal transduction processes, and a dynamic representation through computer simulation. Moreover, it provides the required power to process the increasing amount of information emerging from the fields of genomics and proteomics, and from the use of new technologies such as microarray analysis. In this review, we have used the Boolean language to represent and analyze part of the signaling network of disease resistance in Arabidopsis.