Network Structure and Dynamics, and Emergence of Robustness by Stabilizing Selection in an Artificial Genome

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dc.creatorRohlf, Thimo
dc.creatorWinkler, Chris
dc.date2008-04-30
dc.date.accessioned2026-07-07T09:35:59Z
dc.date.available2026-07-07T09:35:59Z
dc.descriptionGenetic regulation is a key component in development, but a clear understanding of the structure and dynamics of genetic networks is not yet at hand. In this work we investigate these properties within an artificial genome model originally introduced by Reil. We analyze statistical properties of randomly generated genomes both on the sequence- and network level, and show that this model correctly predicts the frequency of genes in genomes as found in experimental data. Using an evolutionary algorithm based on stabilizing selection for a phenotype, we show that robustness against single base mutations, as well as against random changes in initial network states that mimic stochastic fluctuations in environmental conditions, can emerge in parallel. Evolved genomes exhibit characteristic patterns on both sequence and network level.
dc.description7 pages, 7 figures. Submitted to the "8th German Workshop on Artificial Life (GWAL 8)"
dc.identifierhttps://arxiv.org/abs/0804.4714
dc.identifierhttp://arxiv.org/abs/0804.4714
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/160016
dc.subjectMolecular Networks
dc.subjectDisordered Systems and Neural Networks
dc.subjectNeural and Evolutionary Computing
dc.subjectGenomics
dc.subjectPopulations and Evolution
dc.titleNetwork Structure and Dynamics, and Emergence of Robustness by Stabilizing Selection in an Artificial Genome
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