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Computational morphodynamics of plants: integrating development over space and time

Abstract

The emerging field of computational morphodynamics aims to understand the changes that occur in space and time during development by combining three technical strategies: live imaging to observe development as it happens; image processing and analysis to extract quantitative information; and computational modelling to express and test time-dependent hypotheses. The strength of the field comes from the iterative and combined use of these techniques, which has provided important insights into plant development.

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Figure 1: Gene regulatory networks.
Figure 2: The iterative process of imaging, image processing and modelling in sepal patterning.
Figure 3: Mechanics.

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Acknowledgements

We apologize to the numerous members of these fields whose work we could not include owing to space limitations. We thank E. Mjolsness, W. Li, Y. Zhou and L. Ben-Ghaly for insightful comments. We acknowledge support from the Gordon and Betty Moore Cell Center at California Institute of Technology, the US National Institutes of Health (grants F32GM090543 to P.T.T. and R01 GM086639 to E.M.M.), the US Department of Energy (grant DE-FG02-88ER13873 to E.M.M.) and the US National Science Foundation (grant IOS-0846192 to E.M.M.).

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Correspondence to Adrienne H. K. Roeder or Elliot M. Meyerowitz.

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Roeder, A., Tarr, P., Tobin, C. et al. Computational morphodynamics of plants: integrating development over space and time. Nat Rev Mol Cell Biol 12, 265–273 (2011). https://doi.org/10.1038/nrm3079

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