The incorporation of epigenetics in artificial gene regulatory networks
Created by W.Langdon from
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- @Article{turner2013incorporation,
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author = "Alexander P. Turner and Michael A. Lones and
Luis A. Fuente and Susan Stepney and Leo S. D. Caves and
Andy M. Tyrrell",
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title = "The incorporation of epigenetics in artificial gene
regulatory networks",
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journal = "Biosystems",
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volume = "112",
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number = "2",
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pages = "56--62",
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year = "2013",
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month = may,
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note = "Selected papers from the 9th International Conference
on Information Processing in Cells and Tissues",
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keywords = "genetic algorithms, genetic programming, Artificial
gene regulation, Epigenetics, Dynamical systems, Chaos
control, Evolutionary algorithms",
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publisher = "Elsevier",
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ISSN = "0303-2647",
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URL = "http://www.sciencedirect.com/science/article/pii/S0303264713000579",
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DOI = "doi:10.1016/j.biosystems.2013.03.013",
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abstract = "Artificial gene regulatory networks are computational
models that draw inspiration from biological networks
of gene regulation. Since their inception they have
been used to infer knowledge about gene regulation and
as methods of computation. These computational models
have been shown to possess properties typically found
in the biological world, such as robustness and self
organisation. Recently, it has become apparent that
epigenetic mechanisms play an important role in gene
regulation. This paper describes a new model, the
Artificial Epigenetic Regulatory Network (AERN) which
builds upon existing models by adding an epigenetic
control layer. Our results demonstrate that AERNs are
more adept at controlling multiple opposing
trajectories when applied to a chaos control task
within a conservative dynamical system, suggesting that
AERNs are an interesting area for further
investigation.",
-
notes = "PMID: 23499812",
- }
Genetic Programming entries for
Alexander P Turner
Michael A Lones
Luis A Fuente
Susan Stepney
Leo Caves
Andrew M Tyrrell
Citations