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access icon openaccess Method for identification of sensitive nodes in Boolean models of biological networks

  • Author(s): Pooja A. Dnyane 1 ; Shraddha S. Puntambekar 1, 2 ; Chetan J. Gadgil 1, 2, 3
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  • Source: Volume 12, Issue 1, February 2018, p. 1 – 6
    DOI:  10.1049/iet-syb.2017.0039 , Print ISSN 1751-8849, Online ISSN 1751-8857
This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial-NoDerivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/)
Received 27/07/2017, Accepted 16/08/2017, Published 04/09/2017

Biological systems are often represented as Boolean networks and analysed to identify sensitive nodes which on perturbation disproportionately change a predefined output. There exist different kinds of perturbation methods: perturbation of function, perturbation of state and perturbation in update scheme. Nodes may have defects in interpretation of the inputs from other nodes and calculation of the node output. To simulate these defects and systematically assess their effect on the system output, two new function perturbations, referred to as ‘not of function’ and ‘function of not’, are introduced. In the former, the inputs are assumed to be correctly interpreted but the output of the update rule is perturbed; and in the latter, each input is perturbed but the correct update rule is applied. These and previously used perturbation methods were applied to two existing Boolean models, namely the human melanogenesis signalling network and the fly segment polarity network. Through mathematical simulations, it was found that these methods successfully identified nodes earlier found to be sensitive using other methods, and were also able to identify sensitive nodes which were previously unreported.

Inspec keywords: perturbation theory; physiological models; Boolean functions

Other keywords: biological networks; perturbation methods; human melanogenesis signalling network; fly segment polarity network; Boolean models

Subjects: Function theory, analysis; General, theoretical, and mathematical biophysics; Systems theory applications in biology and medicine; Algebra, set theory, and graph theory; Algebra; Formal logic

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