title: The complex fluctuations of probabilistic Boolean networks.
abstract: Probabilistic Boolean networks (PBNs) are extensions of Boolean networks (BNs), and both have been widely used to model biological systems. In this paper, we study the long-range correlations of PBNs based on their corresponding Markov chains. PBN states are quantified by the deviation of their steady-state distributions. The results demonstrate that, compared with BNs, PBNs can exhibit these dynamics over a wider and higher noise range. In addition, the constituent BNs significantly impact the generation of 1/f dynamics of PBNs, and PBNs with homogeneous steady-state distributions tend to sustain the 1/f dynamics over a wider noise range.
authors.affiliation: Department of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou 325035, Zhejiang, China.
authors.forename: Yuan-ming
authors.initials: YM
authors.lastname: Gao
authors.forename: Peng
authors.initials: P
authors.lastname: Xu
authors.forename: Xiang-hong
authors.initials: XH
authors.lastname: Wang
authors.forename: Wen-bin
authors.initials: WB
authors.lastname: Liu
mesh_terms: D003198:Computer Simulation; D053263:Gene Regulatory Networks / Q000235:genetics; D008390:Markov Chains; D008954:Models, Biological; D011336:Probability; D011518:Proto-Oncogene Proteins / Q000235:genetics; D049490:Systems Biology / Q000379:methods*; D051153:Wnt Proteins / Q000235:genetics; D000071818:Wnt-5a Protein
chemical_list: D011518:Proto-Oncogene Proteins; C085389:WNT5A protein, human; D051153:Wnt Proteins; D000071818:Wnt-5a Protein
keywords: 1/f dynamics; Long-range correlation; Probabilistic Boolean network