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Algorithms for Analysis and Control of Boolean Networks

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Algorithms for Computational Biology (AlCoB 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10849))

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Abstract

Boolean network is a discrete mathematical model of gene regulatory networks. In this short article, we briefly review algorithmic results on finding attractors in Boolean networks. Since it is known that the problem of finding a singleton attractor is NP-hard and the problem can be trivially solved in \(O^{*}(2^n)\) time (under a reasonable assumption), we focus on special cases in which the problem can be solved in \(O((2-\delta )^n)\) time for some constant \(\delta >0\). We also briefly review algorithmic results on control of Boolean networks.

Partially supported by JSPS, Japan: Grant-in-Aid 26240034.

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Notes

  1. 1.

    \(O^{*}(f(n))\) denotes O(f(n)poly(n)).

References

  1. Akutsu, T.: Algorithms for Analysis, Inference, and Control of Boolean Networks. World Scientific, Singapore (2018)

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  2. Cheng, D., Qi, H., Li, Z.: Analysis and Control of Boolean Networks: A Semi-tensor Product Approach. Springer, London (2011). https://doi.org/10.1007/978-0-85729-097-7

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  3. Kauffman, S.A.: Homeostasis and differentiation in random genetic control networks. Nature 224, 177–178 (1969)

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  4. Lu, J., Li, H., Liu, Y., Li, F.: Survey on semi-tensor product method with its applications in logical networks and other finite-valued systems. IET Control Theory Appl. 11, 2040–2047 (2017)

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Author information

Authors and Affiliations

  1. Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan

    Tatsuya Akutsu

Authors
  1. Tatsuya Akutsu
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Correspondence to Tatsuya Akutsu .

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Editors and Affiliations

  1. The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Jesper Jansson

  2. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  3. University of Extremadura, Cáceres, Spain

    Miguel A. Vega-Rodríguez

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Akutsu, T. (2018). Algorithms for Analysis and Control of Boolean Networks. In: Jansson, J., Martín-Vide, C., Vega-Rodríguez, M. (eds) Algorithms for Computational Biology. AlCoB 2018. Lecture Notes in Computer Science(), vol 10849. Springer, Cham. https://doi.org/10.1007/978-3-319-91938-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-91938-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91937-9

  • Online ISBN: 978-3-319-91938-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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