savageau/dst3 repository overview

⁠The Design Space & The Design Space Toolbox

Mechanistic models of biochemical systems provide a rigorous kinetics-based description of various biological phenomena. They are indispensable to elucidate biological design principles and to devise and engineer systems with novel functionalities. To date, mathematical analysis and characterization of these models remain a challenging endeavor, the main difficulty being the lack of information for most system parameters. Here, we introduce the Design Space Toolbox v.3.0 (DST3)[9], a software implementation of the Design Space formalism that enables mechanistic modeling of complex 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. The Design Space methodology and its software implementations have been developed over the last decade (for examples of this methodology, see [1-9]). The method was originally conceived by Michael A. Savageau in 2009 [1-2]. DST3 represents the most generally applicable implementation of the Design Space formalism to date and offers unique advantages over earlier versions [3,7]. By expanding the capabilities of the Design Space formalism and streamlining its distribution, DST3 represents a valuable tool for elucidating biological design principles and guiding the design and optimization of novel synthetic circuits.

⁠Docker Image

This repository contains a stable version of the Design Space Toolbox V3 (DST3). See Tags tab for details. DST3 is currently under development by Miguel A. Valderrama-Gómez ([email protected]⁠) in the Savageau Laboratory (https://savageaulab.wordpress.com/⁠) @ UC Davis

⁠Getting Started

To use the DST3 Docker Image:

1. Download Image: docker pull savageau/dst3

2. Create Container: docker run -d -p 8888:8888 savageau/dst3

3. Open http://localhost:8888⁠ in a browser window

see special instructions for Windows users: https://savageaulab.wordpress.com/docker-image-for-the-design-space-toolbox-v3/⁠

The Ipython Notebooks contained in the folder /Tutorials/Tutorial_DST3 provides an introduction to the widget-based user interface of the DST3, which provides access to the core functionalities of the DST3.

Current software development and maintenance is being performed by Miguel Á. Valderrama-Gómez ([email protected]⁠).

⁠References

1. Savageau MA, Coelho PMBM, Fasani RA, Tolla DA, and Salvador A (2009) Phenotypes and tolerances in the design space of biochemical systems. Proc. Natl. Acad. Sci. U.S.A. 106, 6435–6440.

2. Savageau MA, Fasani RA (2009) Qualitatively distinct phenotypes in the design space of biochemical systems. FEBS Lett. Dec 17;583(24):3914-22. Epub. Review. PubMed PMID: 19879266; PubMed Central PMCID: PMC2888490.

3. Fasani RA, and Savageau MA (2010) Automated construction and analysis of the design space for biochemical systems. Bioinformatics 26:2601–2609.

4. Savageau MA, and Lomnitz JG (2013) Deconstructing Complex Nonlinear Models in System Design Space, in Discrete and Topological Models in Molecular Biology (Jonoska, N., and Saito, M., Eds.). Springer.

5. Lomnitz JG, and Savageau, MA (2013) Phenotypic deconstruction of gene circuitry. Chaos 23, 025108.

6. Lomnitz JG, and Savageau MA (2014) Strategy Revealing Phenotypic Differences among Synthetic Oscillator Designs. ACS Synth Biol 3(9):686–701.

7. Lomnitz JG, Savageau MA (2016) Design Space Toolbox V2: Automated software enabling a novel phenotype-centric modeling strategy for natural and synthetic biological systems. Front. Genet. 7, 118.

8. Valderrama-Gómez MA, Parales RE and Savageau MA (2018) Phenotype-centric modeling for elucidation of biological design principles. J. Theor. Biol. 455:281-292

9. Valderrama-Gómez MA, Lomnitz GA, Fasani RA, Savageau MA (2020) Mechanistic Modeling of Biochemical Systems Without A Priori Parameter Values Using the Design Space Toolbox v.3.0. iScience, 101200. https://doi.org/10.1016/j.isci.2020.101200⁠