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Evolving Scale-Free Topologies using a Gene Regulatory Network Model
Author(s)
Date Issued
2008-06-06
Date Available
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.
Sponsorship
European Commission
Other Sponsorship
Sixth European Research Framework
Type of Material
Conference Publication
Publisher
IEEE
Start Page
3747
End Page
3754
Copyright (Published Version)
2008 IEEE
Language
English
Status of Item
Peer reviewed
Conference Details
IEEE Congress on Evolutionary Computation (CEC 2008) Hong-Kong, China, 1-6 June 2008
This item is made available under a Creative Commons License
File(s)
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Name
nicolau08a.pdf
Size
2.63 MB
Format
Adobe PDF
Checksum (MD5)
7257be210766fe43d96f318f046226cd
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