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Easybiotics: a GUI for 3D physical modelling of multi-species bacterial populations

Lookup NU author(s): Jonny Naylor, Dr Harold Fellermann, Professor Natalio Krasnogor

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Abstract

Motivation3D physical modelling is a powerful computational technique that allows for the simulation of complex systems such as consortia of mixed bacterial species. The complexities in physical modelling reside in the knowledge intensive model building process and the computational expense in calculating their numerical solutions. These models can offer insights into microbiology, both in understanding natural systems and as design tools for developing novel synthetic bacterial systems. Developing a robust synthetic system typically requires multiple iterations around the specify→design→build→test cycle to meet specifications. This process is laborious and expensive for both the computational and laboratory aspects, hence any improvement in any of the workflow steps would be welcomed. We have previously introduced Simbiotics, a powerful and flexible platform for designing and analyzing 3D simulations of mixed species bacterial populations. Simbiotics requires programming experience to use which creates barriers to entry for use of the tool.ResultsIn the spirit of enabling biologists who may not have programming skills to install and utilize Simbiotics, we present in this application note Easybiotics, a user-friendly graphical user interface for Simbiotics. Users may design, simulate and analyze models from within the graphical user interface, with features such as live graph plotting and parameter sweeps. Easybiotics provides full access to all of Simbiotics simulation features, such as cell growth, motility and gene regulation.Availability and implementationEasybiotics and Simbiotics are free to use under the GPL3.0 licence, and can be found at: http://ico2s.org/software/simbiotics.html. We also provide readily downloadable virtual machine sandboxes to facilitate rapid installation.


Publication metadata

Author(s): Naylor J, Fellermann H, Krasnogor N

Publication type: Article

Publication status: Published

Journal: Bioinformatics

Year: 2019

Pages: Epub ahead of print

Online publication date: 23/02/2019

Acceptance date: 21/02/2019

ISSN (print): 1367-4803

ISSN (electronic): 1460-2059

Publisher: Oxford University Press

URL: https://doi.org/10.1093/bioinformatics/btz131

DOI: 10.1093/bioinformatics/btz131


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