A field known as Systems Biology is emerging, from roots in the molecular biology and genomic biology revolutions-the succession of which has led biomedical scientists to recognize that living systems can be studied not only in terms of their mechanistic, molecular-level components but also in terms of many of them simultaneously. This prospect of understanding how biological entities function through the framework of integrated operation of component parts holds extraordinary promise for medical applications, as well for broader societal applications such as the environment, agriculture, materials/manufacturing, and national defense.Some definitions of Systems Biology are available. Ideker et al. 22 suggest the following: "Systems Biology does not investigate individual genes or proteins one at a time, as has been the highly successful mode of biology for the past 30 years. Rather, it investigates the behavior and relationships of all the elements in a particular biological system while it is functioning." A description by Kitano 27 is that "To understand biology at the system level, we must examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism." The National Institute of General Medical Sciences at NIH 1 provides a slightly different perspective: "Systems Biology seeks to predict the quantitative behavior of an in vivo biological process under realistic perturbation, where the quantitative treatment derives its power from explicit inclusion of the process components, their interactions, and realistic values for their concentrations, locations, and local states."Systems Biology can also be defined operationally, as by the MIT Computational & Systems Biology Initiative, in terms of the "4 M's"-Measurement, Mining, Modeling, and Manipulation-illustrated schematically in Fig. 1 (see http://csbi.mit.edu/). In this post-genomic era, Measurement can be undertaken in a high-throughput, multivariate manner using various kinds of array technologies. Because this multivariate data then is relatively recalcitrant to hypothesis generation by means of unaided human intuition, Address correspondence to A. Douglas Lauffenburger, Biological Engineering Division, Massachusetts Institute of Technology computational algorithms for Mining the data to generate hypotheses concerning the potential interpretation of these data sets is necessary. In order to consequently develop new predictions for experimental test (or design), computational Modeling is required for similar reason: unaided human intuition likely cannot produce effective predictions concerning complex, interconnected, nonlinear molecular systems. Finally, in order to test those model predictions or create a new technology or product, molecular-level manipulation is needed, employing genetic, biochemical, or materials interventions. Thus, Systems Biology involves a multivariate approach comprising topological and dynamical properties and aimed ultimately at quantitative prediction, ...

A field known as Systems Biology is emerging, from roots in the molecular biology and genomic biology revolutions-the succession of which has led biomedical scientists to recognize that living systems can be studied not only in terms of their mechanistic, molecular-level components but also in terms of many of them simultaneously. This prospect of understanding how biological entities function through the framework of integrated operation of component parts holds extraordinary promise for medical applications, as well for broader societal applications such as the environment, agriculture, materials/manufacturing, and national defense.Some definitions of Systems Biology are available. Ideker et al. 22 suggest the following: "Systems Biology does not investigate individual genes or proteins one at a time, as has been the highly successful mode of biology for the past 30 years. Rather, it investigates the behavior and relationships of all the elements in a particular biological system while it is functioning." A description by Kitano 27 is that "To understand biology at the system level, we must examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism." The National Institute of General Medical Sciences at NIH 1 provides a slightly different perspective: "Systems Biology seeks to predict the quantitative behavior of an in vivo biological process under realistic perturbation, where the quantitative treatment derives its power from explicit inclusion of the process components, their interactions, and realistic values for their concentrations, locations, and local states. Address correspondence to Douglas A. Lauffenburger, Biological Engineering Division, Massachusetts Institute of Technology ment can be undertaken in a high-throughput, multivariate manner using various kinds of array technologies. Because this multivariate data then is relatively recalcitrant to hypothesis generation by means of unaided human intuition, computational algorithms for Mining the data to generate hypotheses concerning the potential interpretation of these data sets is necessary. In order to consequently develop new predictions for experimental test (or design), computational Modeling is required for similar reason: unaided human intuition likely cannot produce effective predictions concerning complex, interconnected, nonlinear molecular systems. Finally, in order to test those model predictions or create a new technology or product, molecular-level Manipulation is needed, employing genetic, biochemical, or materials interventions. Thus, Systems Biology involves a multivariate approach comprising topological and dynamical properties and aimed ultimately at quantitative prediction, for basic scientific understanding or technological design. It must be noted that the complexity of living systems does not reside solely in the number of components and interactions treated, nor in their associated structural and physicochemical properties, but also in the hi...