Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800136
Title: Visualization in the synthetic biology design cycle
Author: Scott-Brown, James
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2019
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Abstract:
Synthetic biology is an emerging field with the ultimate aim of designing and building biological systems with particular functions. Achieving this goal requires parallel developments in several areas: experimental methods, libraries of reusable parts mined from natural systems, approaches to mathematical modelling, and design tools. As the biological circuits that are designed and built become more complex, automation becomes increasingly important at every stage. Appropriate use of visualization can facilitate the development of synthetic biology by aiding both the understanding of data and interaction with automation tools. This thesis therefore introduces visual tools for several tasks in the synthetic biology design-build-test-cycle, using diagrammatic representations that are designed to be clear to human readers whilst also having a precise meaning. These tools are intended to enable the expression of temporal logic specifications, the identification of models and parameters that cause these specifications to be satisfied, and the expression of laboratory protocols that could be used to experimentally test the resulting designs. In this thesis we first develop two diagrammatic representations: the TimeRails representation of specifications provides an abstraction for representing sets of signals, and the List of Liquids representation provides a representation of laboratory protocols for conducting experiments. This thesis also describes two approaches for the automated design of a circuit to meet a specification expressed using TimeRails. The first approach constructs a satisfaction problem modulo the theory of Ordinary Differential Equations. The second approach uses Approximate Bayesian Computation to sample from the posterior distribution over parameters, given that the system meets the specification; the results of this inference process are presented in a visual tool that can also be applied to model selection and parameter estimation more generally.
Supervisor: Papachristodoulou, Antonis Sponsor: Engineering and Physical Sciences Research Council ; DSTL
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.800136  DOI: Not available
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