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Bilevel integer programming on a Boolean network for discovering critical genetic alterations in cancer development and therapy

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  • Moon, Kyungduk
  • Lee, Kangbok
  • Chopra, Sunil
  • Kwon, Steve

Abstract

Boolean network is a modeling tool that describes a dynamic system with binary variables and their logical transition formulas. Recent studies in precision medicine use a Boolean network to discover critical genetic alterations that may lead to cancer or target genes for effective therapies to individuals. In this paper, we study a logical inference problem in a Boolean network to find all such critical genetic alterations in a minimal (parsimonious) way. We propose a bilevel integer programming model to find a single minimal genetic alteration. Using the bilevel integer programming model, we develop a branch and bound algorithm that effectively finds all of the minimal alterations. Through a computational study with eleven Boolean networks from the literature, we show that the proposed algorithm finds solutions much faster than the state-of-the-art algorithms in large data sets.

Suggested Citation

  • Moon, Kyungduk & Lee, Kangbok & Chopra, Sunil & Kwon, Steve, 2022. "Bilevel integer programming on a Boolean network for discovering critical genetic alterations in cancer development and therapy," European Journal of Operational Research, Elsevier, vol. 300(2), pages 743-754.
    • Handle: RePEc:eee:ejores:v:300:y:2022:i:2:p:743-754
    DOI: 10.1016/j.ejor.2021.10.019
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    References listed on IDEAS

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    4. Liu, Shaonan & Wang, Mingzheng & Kong, Nan & Hu, Xiangpei, 2021. "An enhanced branch-and-bound algorithm for bilevel integer linear programming," European Journal of Operational Research, Elsevier, vol. 291(2), pages 661-679.
    5. H. Paul Williams, 2009. "Modelling In Logic For Integer Programming," International Series in Operations Research & Management Science, in: Logic and Integer Programming, chapter 0, pages 71-103, Springer.
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