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Living on the edges

Nature Biotechnology volume 19, pages 111–112 (2001)Cite this article

We all marvel at the intricacies and beauty of even the simplest of living cells, not to mention the breathtaking panorama of curves displayed by organisms of more complex extension. And many have enjoyed (and indeed forged quite successful careers) discovering the multitude of molecular components that compose the typical cell, and inferring, correctly or not, their possible functions. Simultaneously, over the past decades, a few far-thinking biophysicists1,2 and biochemical engineers3,4 have attempted to use the methods of systems analysis to try to make sense of the sometimes labyrinthine-appearing interactions between these components. These approaches rely on the formulation of detailed kinetic models of cellular interactions, and such models have played a critical role in the development of metabolic engineering from an almost unknown term a decade ago to one of the leading edges of biotechnology5. Jay Bailey, an inspirational force in both the conceptualization and the actualization of these approaches, has given particularly illuminating personal accounts of the use of mathematical models in metabolic engineering4,6.

However, model-building efforts of this type have been hampered primarily by two requirements: to get a complete enumeration of the molecular players involved and to obtain the necessary kinetic information for dynamic simulations. Although much progress is being made concerning the first of these (in particular, the art of reconstructing metabolic networks on a genome-wide scale has reached an advanced stage7), the second issue remains a major challenge, although one web site containing large amounts of kinetic information has now appeared8.

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Figure 1: Contrasting two methods of modeling the behavior of a cell.

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  1. a resident scholar at the Institute of Biotechnology, Autonomous National University of Mexico, Cuernavaca, Mexico

    Harvey Bialy

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  1. Harvey Bialy
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Bialy, H. Living on the edges. Nat Biotechnol 19, 111–112 (2001). https://doi.org/10.1038/84352

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