Abstract
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.
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Velderraín, J.D., Martínez-García, J.C., Álvarez-Buylla, E.R. (2017). Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction. In: Kaufmann, K., Mueller-Roeber, B. (eds) Plant Gene Regulatory Networks. Methods in Molecular Biology, vol 1629. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7125-1_19
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DOI: https://doi.org/10.1007/978-1-4939-7125-1_19
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