Modern systems biology and synthetic bioengineering face two major challenges in relating properties of the genetic components of a natural or engineered system to its integrated behavior. The first is the fundamental unsolved problem of relating the digital representation of the genotype to the analog representation of the parameters for the molecular components. For example, knowing the DNA sequence does not allow one to determine the kinetic parameters of an enzyme. The second is the fundamental unsolved problem of relating the parameters of the components and the environment to the phenotype of the global system. For example, knowing the parameters does not tell one how many qualitatively distinct phenotypes are in the organism’s repertoire or the relative fitness of the phenotypes in different environments. These also are challenges for biomedical engineers as they attempt to develop therapeutic strategies to treat pathology or to redirect normal cellular functions for biotechnological purposes. In this article, the second of these fundamental challenges will be addressed, and the notion of a “system design space” for relating the parameter space of components to the phenotype space of bioengineering systems will be focused upon. First, the concept of a system design space will be motivated by introducing one of its key components from an intuitive perspective. Second, a simple linear example will be used to illustrate a generic method for constructing the design space in which qualitatively distinct phenotypes can be identified and counted, their fitness analyzed and compared, and their tolerance to change measured. Third, two examples of nonlinear systems from different areas of biomedical engineering will be presented. Finally, after giving reference to a few other applications that have made use of the system design space approach to reveal important design principles, some concluding remarks concerning challenges and opportunities for further development will be made.
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I thank Julie Sutcliffe as well as Erik Welf and Jason Haugh for sharing figures from their study, Rick Fasani for assistance in constructing the system design spaces, and Pedro Coelho, Dean Tolla, Phillip Seitzer, and Jason Lomnitz for their fruitful discussions. I also wish to thank the anonymous reviewers who made comments and suggestions that helped in substantially improving the manuscript. This study was supported in part by the U.S. Public Health Service Grant R01-GM30054, and by a Stanislaw Ulam Distinguished Scholar Award from the Center for Non-Linear Studies of the Los Alamos National Laboratory.
Author information Authors and AffiliationsDepartment of Biomedical Engineering, The University of California, One Shields Avenue, Davis, CA, 95616-5294, USA
Michael A. Savageau
Correspondence to Michael A. Savageau.
Additional informationAssociate Editor Angelique Louie oversaw the review of this article.
About this article Cite this articleSavageau, M.A. Biomedical Engineering Strategies in System Design Space. Ann Biomed Eng 39, 1278–1295 (2011). https://doi.org/10.1007/s10439-010-0220-2
Received: 30 September 2010
Accepted: 22 November 2010
Published: 04 January 2011
Issue Date: April 2011
DOI: https://doi.org/10.1007/s10439-010-0220-2
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