Authors:
J. S. Hallinan
;
A. Wipat
and
S. Park
Affiliation:
Newcastle University, United Kingdom
Keyword(s):
Synthetic biology, Evolutionary computation, Directed evolution, Genome-scale design.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Biostatistics and Stochastic Models
;
Computational Intelligence
;
Data Mining and Machine Learning
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Methodologies and Technologies
;
Operational Research
;
Simulation
;
Soft Computing
Abstract:
Computational design is essential to the field of synthetic biology, particularly as its practitioners become more ambitious, and system designs become larger and more complex. However, computational models derived from abstract designs are unlikely to behave in the same way as organisms engineered from those same designs. We propose an automated, iterative strategy involving evolution both in silico and in vivo, with feedback between strands as necessary, combined with automated reasoning. This system can help bridge the gap between the behaviour of computational models and that of engineered organisms in as rapid and cost-effective a manner as possible.