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Title: Effect of memory in non-Markovian Boolean networks illustrated with a case study: A cell cycling process
Authors: Ebadi, Haleh
Saeedian, Meghdad
Ausloos, Marcel
Jafari, Gholam Reza
First Published: 20-Dec-2016
Publisher: European Physical Society, EDP Sciences, Società Italiana di Fisica, IOP Publishing, EPL Association
Citation: EPL (Europhysics Letters), 2016,116 (3)
Abstract: One successful model of interacting biological systems is the Boolean network. The dynamics of a Boolean network, controlled with Boolean functions, is usually considered to be a Markovian (memory-less) process. However, both self organizing features of biological phenomena and their intelligent nature should raise some doubt about ignoring the history of their time evolution. Here, we extend the Boolean network Markovian approach: we involve the effect of memory on the dynamics. This can be explored by modifying Boolean functions into non-Markovian functions, for example, by investigating the usual non-Markovian threshold function, - one of the most applied Boolean functions. By applying the non-Markovian threshold function on the dynamical process of a cell cycle network, we discover a power law memory with a more robust dynamics than the Markovian dynamics.
DOI Link: 10.1209/0295-5075/116/30004
ISSN: 0295-5075
eISSN: 1286-4854
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016, European Physical Society, EDP Sciences, Società Italiana di Fisica, IOP Publishing, EPL Association. Deposited with reference to the publisher’s open access archiving policy.
Description: The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
Appears in Collections:Published Articles, School of Management

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