Evolving Scale-Free Topologies using a Gene Regulatory Network Model

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Title: Evolving Scale-Free Topologies using a Gene Regulatory Network Model
Authors: Nicolau, Miguel
Schoenauer, Marc
Permanent link: http://hdl.handle.net/10197/8261
Date: 6-Jun-2008
Online since: 2017-01-13T15:31:00Z
Abstract: A novel approach to generating scale-free network topologies is introduced, based on an existing artificial Gene Regulatory Network model. From this model, different interaction networks can be extracted, based on an activation threshold. By using an Evolutionary Computation approach, the model is allowed to evolve, in order to reach specific network statistical measures. The results obtained show that, when the model uses a duplication and divergence initialisation, such as seen in nature, the resulting regulation networks not only are closer in topology to scale-free networks, but also exhibit a much higher potential for evolution.
Funding Details: European Commission
Type of material: Conference Publication
Publisher: IEEE
Start page: 3747
End page: 3754
Copyright (published version): 2008 IEEE
Keywords: Scale-free topologiesComplex networksEvolutionary computation
DOI: 10.1109/cec.2008.4631305
Language: en
Status of Item: Peer reviewed
Conference Details: IEEE Congress on Evolutionary Computation (CEC 2008) Hong-Kong, China, 1-6 June 2008
Appears in Collections:Business Research Collection

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