title: Computational modelling of the BRI1 receptor system.
abstract: Computational models are useful tools to help understand signalling pathways in plant cells. A systems biology approach where models and experimental data are combined can provide experimentally verifiable predictions and novel insights. The brassinosteroid insensitive 1 (BRI1) receptor is one of the best-understood receptor systems in Arabidopsis with clearly described ligands, mutants and associated phenotypes. Therefore, BRI1-mediated signalling is attractive for mathematical modelling approaches to understand and interpret the spatial and temporal dynamics of signal transduction cascades in planta. To establish such a model, quantitative data sets incorporating local protein concentration, binding affinity and phosphorylation state of the different pathway components are essential. Computational modelling is increasingly employed in studies of plant growth and development. In this section, we have focused on the use of quantitative imaging of fluorescently labelled proteins as an entry point in modelling studies.
authors: Department of Biochemistry, Wageningen University, Wageningen, The Netherlands. wilma.vanesse@wur.nl
authors: G Wilma
authors: GW
authors: van Esse
authors: Klaus
authors: K
authors: Harter
authors: Sacco C
authors: SC
authors: de Vries
mesh_terms: D017360:Arabidopsis / Q000378:metabolism*; D029681:Arabidopsis Proteins / Q000378:metabolism*; D060406:Brassinosteroids / Q000378:metabolism; D008954:Models, Biological; D011494:Protein Kinases / Q000378:metabolism*; D020239:Receptor Cross-Talk; D015398:Signal Transduction
chemical_list: D029681:Arabidopsis Proteins; D060406:Brassinosteroids; D011494:Protein Kinases; C108270:BRI1 protein, Arabidopsis
keywords: brassinosteroids; growth; hormones; imaging; microscopy; modelling