Advances in experimental techniques and tools applicable to computational biology have spurred great expectations in the field of cell simulation and have allowed scientists to probe deeper into ever more complex systems. The development of research strategies capable of integrating the various data types currently in use and of producing cohesive information is essential for providing further insights into such systems. Systems biology attempts to integrate individual components and analyze a system, e.g.,, cells and organisms as a whole, in order lo understand and predict properties globally. Over the past decade, applications in systems biology have mainly focused on bacteria such as Escherichia coli because of their simplicity and the availability of abundant data, and on human cells because of their importance for medical applications (myocardial cells, erythrocyles). As methods in computational biology become established, attention has also turned towards cukaryotic systems including plants. However, the multi-dimensionality of eukaryotic organisms, their sheer size, and their complexity present difficulties in plant cell modeling and simulation. The application of systems biology to plants in order to automate and efficiently analyze available data will facilitate the generation of predictions, and aid in the engineering of plants and microorganisms.
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