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Composable Modular Models for Synthetic Biology

Lookup NU author(s): Dr Goksel Misirli, Dr Jennifer Hallinan, Professor Anil Wipat

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This is the final published version of a report that has been published in its final definitive form by School of Computing Science, University of Newcastle upon Tyne, 2014.

For re-use rights please refer to the publisher's terms and conditions.

Abstract

Modelling and computational simulation are crucial for the large-scale engineering of biological circuits since they allow the system under design to be simulated prior to implementation in vivo. To support automated, model-driven design it is desirable that in silico models are modular, composable and use standard formats. The synthetic biology design process typically involves the composition of genetic circuits from individual parts. At the most basic level these parts are representations of genetic features such as promoters, ribosome binding sites (RBSs), and coding sequences (CDSs). However, it is also desirable to model the biological molecules and behaviour that arise when these parts are combined in vivo. Modular models of parts can be composed and their associated systems simulated, facilitating the process of model centred design. The availability of databases of modular models is essential to support software tools used in the model-driven design process. In this paper we present an approach to support the development of composable, modular models for synthetic biology, termed Standard Virtual Parts. We then describe a programmatically accessible and publicly available database of these models to allow their use by computational design tools.

Publication metadata

Author(s): Misirli G, Hallinan J, Wipat A

Publication type: Report

Publication status: Published

Series Title: School of Computing Science Technical Report Series

Year: 2014

Pages: 20

Print publication date: 01/06/2014

Report Number: 1424

Institution: School of Computing Science, University of Newcastle upon Tyne

Place Published: Newcastle upon Tyne

URL: http://www.cs.ncl.ac.uk/publications/trs/papers/1424.pdf

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