Browse by author
Lookup NU author(s): Professor Anil Wipat
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© Engineering genetic regulatory circuits is key to the creation of biological applications that are responsive to environmental changes. Computational models can assist in understanding especially large and complex circuits for which manual analysis is infeasible, permitting a model-driven design process. However, there are still few tools that offer the ability to simulate the system under design. One of the reasons for this is the lack of accessible model repositories or libraries that cater to the modular composition of models of synthetic systems. Here, we present the second version of the Virtual Parts Repository, a framework to facilitate the model-driven design of genetic regulatory circuits, which provides reusable, modular, and composable models. The new framework is service-oriented, easier to use in computational workflows, and provides several new features and access methods. New features include supporting hierarchical designs via a graph-based repository or compatible remote repositories, enriching existing designs, and using designs provided in Synthetic Biology Open Language documents to derive system-scale and hierarchical Systems Biology Markup Language models. We also present a reaction-based modeling abstraction inspired by rule-based modeling techniques to facilitate scalable and modular modeling of complex and large designs. This modeling abstraction enhances the modeling capability of the framework, for example, to incorporate design patterns such as roadblocking, distributed deployment of genetic circuits using plasmids, and cellular resource dependency. The framework and the modeling abstraction presented in this paper allow computational design tools to take advantage of computational simulations and ultimately help facilitate more predictable applications.
Author(s): Mlslrll G, Yang B, James K, Wipat A
Publication type: Article
Publication status: Published
Journal: ACS Synthetic Biology
Year: 2021
Volume: 10
Issue: 12
Pages: 3304-3315
Print publication date: 17/12/2021
Online publication date: 11/11/2021
Acceptance date: 11/11/2021
ISSN (electronic): 2161-5063
Publisher: American Chemical Society
URL: https://doi.org/10.1021/acssynbio.1c00157
DOI: 10.1021/acssynbio.1c00157
Altmetrics provided by Altmetric
