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Lookup NU author(s): Dr Tim RudgeORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2022 The Authors. Published by American Chemical Society. Genetic design automation tools are necessary to expand the scale and complexity of possible synthetic genetic networks. These tools are enabled by abstraction of a hierarchy of standardized components and devices. Abstracted elements must be parametrized from data derived from relevant experiments, and these experiments must be related to the part composition of the abstract components. Here we present Logical Operators for Integrated Cell Algorithms (LOICA), a Python package for designing, modeling, and characterizing genetic networks based on a simple object-oriented design abstraction. LOICA uses classes to represent different biological and experimental components, which generate models through their interactions. These models can be parametrized by direct connection to data contained in Flapjack so that abstracted components of designs can characterize themselves. Models can be simulated using continuous or stochastic methods and the data published and managed using Flapjack. LOICA also outputs SBOL3 descriptions and generates graph representations of genetic network designs.
Author(s): Vidal G, Vitalis C, Rudge TJ
Publication type: Article
Publication status: Published
Journal: ACS Synthetic Biology
Year: 2022
Volume: 11
Issue: 5
Pages: 1984-1990
Print publication date: 20/05/2022
Online publication date: 04/05/2022
Acceptance date: 02/04/2018
Date deposited: 14/02/2025
ISSN (electronic): 2161-5063
Publisher: American Chemical Society
URL: https://doi.org/10.1021/acssynbio.1c00603
DOI: 10.1021/acssynbio.1c00603
PubMed id: 35507566
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