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Representation of gene regulation networks by hypothesis logic-based Boolean systems.

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Title: Representation of gene regulation networks by hypothesis logic-based Boolean systems.
Authors: Siegel, Pierre1 (AUTHOR), Doncescu, Andrei2 (AUTHOR) andrei.doncescu@laas.fr, Risch, Vincent1 (AUTHOR), Sené, Sylvain1 (AUTHOR)
Source: Journal of Supercomputing. Mar2023, Vol. 79 Issue 4, p4556-4581. 26p.
Subjects: Genetic regulation, Propositional calculus, Modal logic, Limit cycles, Dynamical systems
Abstract: Boolean Dynamical Systems (BDSs) are networks described by Boolean variables. A new representation of BDSs is presented in this article by using modal non-monotonic logic (H ). This approach allows Boolean Networks to be represented by a set of modal formulas and therefore can be used to describe and learn their properties. The study of a BDS focuses in particular on the search of stable configurations, limit cycles and unstable cycles, which help to characterize a large type of Gene Networks. In this article is presented the identification of such asymptotic properties by introduction of a new concept, ghost extensions. Using ghost extensions, it is possible to translate BDSs in propositional calculus and consequently to use SAT algorithms. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Representation of gene regulation networks by hypothesis logic-based Boolean systems.
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  Data: <searchLink fieldCode="AR" term="%22Siegel%2C+Pierre%22">Siegel, Pierre</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Doncescu%2C+Andrei%22">Doncescu, Andrei</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> andrei.doncescu@laas.fr</i><br /><searchLink fieldCode="AR" term="%22Risch%2C+Vincent%22">Risch, Vincent</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sené%2C+Sylvain%22">Sené, Sylvain</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>. Mar2023, Vol. 79 Issue 4, p4556-4581. 26p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Genetic+regulation%22">Genetic regulation</searchLink><br /><searchLink fieldCode="DE" term="%22Propositional+calculus%22">Propositional calculus</searchLink><br /><searchLink fieldCode="DE" term="%22Modal+logic%22">Modal logic</searchLink><br /><searchLink fieldCode="DE" term="%22Limit+cycles%22">Limit cycles</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamical+systems%22">Dynamical systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Boolean Dynamical Systems (BDSs) are networks described by Boolean variables. A new representation of BDSs is presented in this article by using modal non-monotonic logic (H ). This approach allows Boolean Networks to be represented by a set of modal formulas and therefore can be used to describe and learn their properties. The study of a BDS focuses in particular on the search of stable configurations, limit cycles and unstable cycles, which help to characterize a large type of Gene Networks. In this article is presented the identification of such asymptotic properties by introduction of a new concept, ghost extensions. Using ghost extensions, it is possible to translate BDSs in propositional calculus and consequently to use SAT algorithms. [ABSTRACT FROM AUTHOR]
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  Label:
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  Data: <i>Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1007/s11227-022-04809-5
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      – Code: eng
        Text: English
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        PageCount: 26
        StartPage: 4556
    Subjects:
      – SubjectFull: Genetic regulation
        Type: general
      – SubjectFull: Propositional calculus
        Type: general
      – SubjectFull: Modal logic
        Type: general
      – SubjectFull: Limit cycles
        Type: general
      – SubjectFull: Dynamical systems
        Type: general
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      – TitleFull: Representation of gene regulation networks by hypothesis logic-based Boolean systems.
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            NameFull: Siegel, Pierre
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            NameFull: Doncescu, Andrei
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            NameFull: Risch, Vincent
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            – D: 01
              M: 03
              Text: Mar2023
              Type: published
              Y: 2023
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              Value: 79
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            – TitleFull: Journal of Supercomputing
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