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Information Surfaces in Systems Biology and Applications to Engineering Sustainable Agriculture

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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Hesam Dashti, Alireza Siahpirani, James Driver, Amir Assadi. Information Surfaces in Systems Biology and Applications to Engineering Sustainable Agriculture. 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2012, Costa de Caparica, Portugal. pp.77-84, ⟨10.1007/978-3-642-28255-3_9⟩. ⟨hal-01365571⟩

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