Automatic Screening for Perturbations in Boolean Networks
A common approach to address biological questions in systems biology is to simulate regulatory mechanisms using dynamic models. Among others, Boolean networks can be used to model the dynamics of regulatory processes in biology. Boolean network models allow simulating the qualitative behavior of the...
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Published in | Frontiers in physiology Vol. 9; p. 431 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
24.04.2018
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Subjects | |
Online Access | Get full text |
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Summary: | A common approach to address biological questions in systems biology is to simulate regulatory mechanisms using dynamic models. Among others, Boolean networks can be used to model the dynamics of regulatory processes in biology. Boolean network models allow simulating the qualitative behavior of the modeled processes. A central objective in the simulation of Boolean networks is the computation of their long-term behavior-so-called attractors. These attractors are of special interest as they can often be linked to biologically relevant behaviors. Changing internal and external conditions can influence the long-term behavior of the Boolean network model. Perturbation of a Boolean network by stripping a component of the system or simulating a surplus of another element can lead to different attractors. Apparently, the number of possible perturbations and combinations of perturbations increases exponentially with the size of the network. Manually screening a set of possible components for combinations that have a desired effect on the long-term behavior can be very time consuming if not impossible. We developed a method to automatically screen for perturbations that lead to a user-specified change in the network's functioning. This method is implemented in the visual simulation framework ViSiBool utilizing satisfiability (SAT) solvers for fast exhaustive attractor search. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Juilee Thakar, University of Rochester, United States; Kyle B. Gustafson, United States Department of the Navy, United States This article was submitted to Systems Biology, a section of the journal Frontiers in Physiology Edited by: Tomáš Helikar, University of Nebraska-Lincoln, United States |
ISSN: | 1664-042X 1664-042X |
DOI: | 10.3389/fphys.2018.00431 |