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Comparative analysis of bacterial essential and nonessential genes with Hurst exponent based on chaos game representation

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  • Zhou, Qian
  • Yu, Yong-ming

Abstract

Essential genes are indispensable for the survival of an organism. Investigating features associated with gene essentiality is fundamental to the prediction and identification of essential genes with computational techniques. We use fractal theory approach to make comparative analysis of essential and nonessential genes in bacteria. The Hurst exponents of essential genes and nonessential genes available in the DEG database for 27 bacteria are calculated based on their gene chaos game representations. It is found that for most analyzed bacteria, weak negative correlation exists between Hurst exponent and gene length. Moreover, essential genes generally differ from nonessential genes in their Hurst exponent. For genes of similar length, the average Hurst exponent of essential genes is smaller than that of nonessential genes. The results of our work reveal that gene Hurst exponent is very probably useful gene feature for the algorithm predicting essential genes.

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  • Zhou, Qian & Yu, Yong-ming, 2014. "Comparative analysis of bacterial essential and nonessential genes with Hurst exponent based on chaos game representation," Chaos, Solitons & Fractals, Elsevier, vol. 69(C), pages 209-216.
    • Handle: RePEc:eee:chsofr:v:69:y:2014:i:c:p:209-216
    DOI: 10.1016/j.chaos.2014.10.003
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    References listed on IDEAS

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    1. Yu, Z.G. & Anh, V.V. & Wanliss, J.A. & Watson, S.M., 2007. "Chaos game representation of the Dst index and prediction of geomagnetic storm events," Chaos, Solitons & Fractals, Elsevier, vol. 31(3), pages 736-746.
    2. Su, Zhi-Yuan & Wu, Tzuyin & Wang, Shu-Yin, 2009. "Local scaling and multifractal spectrum analyses of DNA sequences – GenBank data analysis," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1750-1765.
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    Cited by:

    1. Zhou, Qian & Qi, Saibing & Ren, Cong, 2021. "Gene essentiality prediction based on chaos game representation and spiking neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).

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