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Mechanistic Modeling of Biochemical Systems Without a Priori Parameter Values Using the Design Space Toolbox v.3.0

55 Pages Posted: 27 Feb 2020 Publication Status: Review Complete

See all articles by Miguel A. Valderrama-Gomez

Miguel A. Valderrama-Gomez

University of California, Davis - Department of Microbiology & Molecular Genetics

Jason G. Lomnitz

VSP Global

Rick A. Fasani

Agilent Technologies

Michael A. Savageau

University of California, Davis - Department of Biomedical Engineering

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Abstract

Mechanistic models of biochemical systems provide a rigorous description of biological phenomena. They are indispensable to elucidate biological design principles. To date, mathematical analysis and characterization of these models remain a challenging endeavor. Here, we introduce the Design Space Toolbox v.3.0 (DST3), a software implementation of the Design Space formalism that enables mechanistic modeling of biological processes without requiring previous knowledge of the parameter values involved. This is achieved by making use of a phenotype-centric modeling approach, in which the system is first decomposed into a series of biochemical phenotypes. Parameter values realizing phenotypes of interest are predicted in a second step. DST3 represents the most generally applicable implementation of the Design Space formalism and offers unique advantages over earlier versions. By expanding the Design Space formalism and streamlining its distribution, DST3 represents a valuable tool for elucidating biological design principles and designing novel synthetic circuits.

Keywords: kinetic parameters, predictive modeling, global analysis, system design principles

Suggested Citation

Valderrama-Gomez, Miguel A. and Lomnitz, Jason G. and Fasani, Rick A. and Savageau, Michael A., Mechanistic Modeling of Biochemical Systems Without a Priori Parameter Values Using the Design Space Toolbox v.3.0. Available at SSRN: https://ssrn.com/abstract=3542578 or http://dx.doi.org/10.2139/ssrn.3542578
This is a paper under consideration at Cell Press and has not been peer-reviewed.

Miguel A. Valderrama-Gomez

University of California, Davis - Department of Microbiology & Molecular Genetics ( email )

Davis, CA 95616
United States

Jason G. Lomnitz

VSP Global

Rancho Cordova, CA 95670
United States

Rick A. Fasani

Agilent Technologies

Santa Clara, CA
United States

Michael A. Savageau (Contact Author)

University of California, Davis - Department of Biomedical Engineering ( email )

United States

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