Medicago truncatula

Immanuel Kant noted this approach would not be suitable for understanding complex systems such as an organism. He said there would never be a " Newton of the blade of grass " : because the blade of grass is more than the sum of its parts, complete knowledge of the parts list will not necessarily be predictive of the behavior of the whole. Fortunately, we don't have to resort to a vitalistic explanation for the phenomenon of emergence. Systems biology offers both an epistemological and technological solution to this problem. Ideker et al. have outlined the four steps of the systems biology approach: component identification and modeling; system perturbation and monitoring; model refining; and model testing. In addition to high-throughput monitoring and reverse-genetics tools, the volume and nature of the data now being generated necessitate the integration of computational modeling and testing. The basic premise is that the identification of a parts list, combined with the monitoring and modeling of the dynamic behavior of those parts, will offer better models of biological systems. The challenge of systems biology. The application of a systems theoretic analysis may dramatically improve our understanding of many biological processes such as morphogenesis, pathogenesis, cognition and ecology. There is no question that these all may be complex systems that preclude full understanding by the reductionistic paradigm. But this new incarnation of systems biology faces a number of challenges in the coming years. The first is technological: to move beyond a focus on transcriptional profiling and protein–protein interactions. A more complete understanding of system dynamics requires knowledge from other parts of the system, such as metabolites, as well as other forms of network modulation, such as post-transcriptional regulation. The second, and perhaps most vexing hurdle, is data sharing. If different datasets are to be integrated in a meaningful way, it will be necessary to not only improve annotations, but also to increase standardization in lab procedures. It is axiomatic in molecular biology that minor variations in procedures, reagents or environment can have a dramatic effect on biological systems. It is thus incumbent on systems biology researchers to communicate more effectively about system parameters that may be relevant to the ultimate model. Lastly, this approach requires expertise in molecular biology, mathematics, genomics, computer science and systems theory. As it is improbable that effective progress in the field will be made by individual researchers with all of these skills, …