Evolving Parameters for a Noisy Biological System – The Impact of Alternative Approaches

Barnes, David J. and Chu, Dominique (2014) Evolving Parameters for a Noisy Biological System – The Impact of Alternative Approaches. In: Artificial Intelligence and Soft Computing 13th International Conference. Lecture Notes in Computer Science, 2 . Springer, Cham, Switzerland, pp. 95-106. ISBN 978-3-319-07175-6. E-ISBN 978-3-319-07176-3. (doi:10.1007/978-3-319-07176-3_9) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:41515)

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Official URL: http://dx.doi.org/10.1007/978-3-319-07176-3_9

Abstract

In this contribution we seek to evolve viable parameter values for a small-scale biological network motif concerned with bacterial nutrient uptake and metabolism. We use two different evolutionary approaches with the model: implicit and explicit. Our results reveal that significantly different characteristics of both efficiency and timescale emerge in the resulting evolved systems depending on the which particular approach is used.

Item Type:	Book section
DOI/Identification number:	10.1007/978-3-319-07176-3_9
Uncontrolled keywords:	genetic algorithm; network motif; genetic algorithm approach; implicit solution; implicit approach
Subjects:	Q Science > Q Science (General) > Q335 Artificial intelligence Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Institutional Unit:	Schools > School of Computing
Former Institutional Unit:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Dominique Chu
Date Deposited:	24 Jun 2014 09:43 UTC
Last Modified:	20 May 2025 10:14 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/41515 (The current URI for this page, for reference purposes)

University of Kent Author Information

Barnes, David J..

Creator's ORCID:	https://orcid.org/0000-0001-6073-0951
CReDIT Contributor Roles:

Chu, Dominique.

Creator's ORCID:	https://orcid.org/0000-0002-3706-2905
CReDIT Contributor Roles:

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