Analysis of preferential network motif generation in an artificial regulatory network model created by duplication and divergence

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@Article{Leier:2007:ACS,

• author = "Andre Leier and Dwight Kuo and Wolfgang Banzhaf",
• title = "Analysis of preferential network motif generation in an artificial regulatory network model created by duplication and divergence",
• journal = "Advances in Complex Systems",
• year = "2007",
• volume = "10",
• number = "2",
• pages = "155--172",
• month = jun,
• keywords = "genetic algorithms, genetic programming, Gene duplication, network motif, gene regulatory networks, artificial regulatory networks",
• ISSN = "0219-5259",
• DOI = "doi:10.1142/S0219525907000994",
• abstract = "Previous studies on network topology of artificial gene regulatory networks created by whole genome duplication and divergence processes show subgraph distributions similar to gene regulatory networks found in nature. In particular, certain network motifs are prominent in both types of networks. In this contribution, we analyze how duplication and divergence processes influence network topology and preferential generation of network motifs. We show that in the artificial model such preference originates from a stronger preservation of protein than regulatory sites by duplication and divergence. If these results can be transferred to regulatory networks in nature, we can infer that after duplication the paralogous transcription factor binding site is less likely to be preserved than the corresponding paralogous protein.",
• notes = "Biological Systems",

}

Genetic Programming entries for Andre Leier P Dwight Kuo Wolfgang Banzhaf

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