Abstract
Systems biology of plants offers myriad opportunities and many challenges in modeling. A number of technical challenges stem from paucity of computational methods for discovery of the fundamental properties of complex dynamical systems in biology. In systems engineering, eigen-mode analysis has proved to be a powerful approach to extract system parameters. Following this philosophy, we introduce a new theory that has the benefits of eigen-mode analysis, while it allows investigation of complex dynamics prior to estimation of optimal scales and resolutions. Information Surfaces organize the many intricate relationships among “eigen-modes” of gene networks at multiple scales. Via an adaptable multi-resolution analytic approach, one could find the appropriate scale and resolution for discovery of functions of genes in plants. This article pertains the model plant Arabidopsis; however, almost all methods can be applied to investigate development and growth of crops for research on sustainable agriculture.
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Dashti, H., Siahpirani, A., Driver, J., Assadi, A.H. (2012). Information Surfaces in Systems Biology and Applications to Engineering Sustainable Agriculture. In: Camarinha-Matos, L.M., Shahamatnia, E., Nunes, G. (eds) Technological Innovation for Value Creation. DoCEIS 2012. IFIP Advances in Information and Communication Technology, vol 372. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28255-3_9
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DOI: https://doi.org/10.1007/978-3-642-28255-3_9
Publisher Name: Springer, Berlin, Heidelberg
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