Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction
Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.
Key wordsSystems biology Gene regulatory networks Cellular differentiation Cell state dynamics Attractor
- 12.Kaplan D, Glass L (2012) Understanding nonlinear dynamics. Springer, New York, NYGoogle Scholar
- 13.Ellner SP, Guckenheimer J (2011) Dynamic models in biology. Princeton University Press, Princeton, NYGoogle Scholar
- 14.Garg A, Mohanram K, De Micheli G, Xenarios I (2012) Implicit methods for qualitative modeling of gene regulatory networks In Gene Regulatory Networks. Humana, New York, NY, pp 397–443Google Scholar
- 15.Espinosa-Soto C, Padilla-Longoria P, Alvarez-Buylla ER (2004) A gene regulatory network model for cell-fate determination during Arabidopsis thaliana flower development that is robust and recovers experimental gene expression profiles. Plant Cell 16(11):2923–2939CrossRefPubMedPubMedCentralGoogle Scholar
- 16.Gershenfeld N (1998) The nature of mathematical modeling. Cambridge University Press, CambridgeGoogle Scholar