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An Investigation of the Structural Stability of Drosophila Control Gene Subnetwork in Computer Experiments

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Bioinformatics of Genome Regulation and Structure

Abstract

We have studied the stability of Drosophila melanogaster gene subnetwork consisting of maternal coordinate and gap genes through computer experiments with a mathematical model developed by the method of generalized threshold models. According to numerical assessments, the Drosophila embryo is heterogeneous from the standpoint of gene network parametric stability in nuclei along the anterior—posterior axis. Our experimental results show that fluctuations in the action thresholds of regulatory substances lower the network parametric stability to a considerably greater extent than fluctuations in the unit intensities of RNA/protein syntheses and degradation. The less is the difference between concentration maximum and minimum values of a certain morphogen (gradient local amplitude) at compartment boundaries, the higher is the model sensitivity to fluctuations in the threshold values of morphogen concentrations. The lowest parametric stability is found at the boundaries between compartments. This can be attributed to gene alternative functioning in the network. The structure of the Drosophila gene network can neutralize mutation phenotypic manifestations. The test procedure of gene network models for parametric stability can be used to identify key genes that make the greatest “contribution” to parametric stability disturbances of the system and to determine the embryo’s compartment boundaries where the gene network displays of low parametric stability.

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Correspondence to A. V. Galimzyanov .

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© 2004 Springer Science+Business Media New York

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Galimzyanov, A.V., Tchuraev, R.N. (2004). An Investigation of the Structural Stability of Drosophila Control Gene Subnetwork in Computer Experiments. In: Kolchanov, N., Hofestaedt, R. (eds) Bioinformatics of Genome Regulation and Structure. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-7152-4_32

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  • DOI: https://doi.org/10.1007/978-1-4419-7152-4_32

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4757-4613-6

  • Online ISBN: 978-1-4419-7152-4

  • eBook Packages: Springer Book Archive

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