Plants, as biological systems, are organized and regulated by a complex network of interactions from the genetic to the morphological level and suffer substantial influence from the environment. Reductionist approaches have been widely used in plant biology but have failed to reveal the mechanisms by which plants can growth under adverse conditions. It seems likely, therefore, that to understand the complexity of plant metabolic responses it is necessary to adopt non-reductionist approaches such as those from systems biology. Although such approaches seem methodologically complex to perform and difficult to interpret, they have been successfully applied in both metabolic and gene expression networks in a wide range of microorganisms and more recently in plants. Given the advance of techniques that allow complex analysis of plant cells, high quantities of data are currently generated and are available for in silico analysis and mathematical modeling. It is increasingly recognized, therefore, that the use of different methods such as graph analysis and dynamic network modeling are needed to better understand this abundance of information. However, before these practical advances, one of the main challenges currently in plant biology is to change the paradigm from the classical reductionism to the systemic level, which requires not only scientific but also educational changes.
Keywords: Biological network; Genome-scale metabolic models; Mathematical modeling; Metabolic fluxes; Systems biology.
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