When correlations matter - response of dynamical networks to small perturbations

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dc.creatorRohlf, Thimo
dc.creatorGulbahce, Natali
dc.creatorTeuscher, Christof
dc.date2008-04-28
dc.date.accessioned2026-07-07T09:35:47Z
dc.date.available2026-07-07T09:35:47Z
dc.descriptionWe systematically study and compare damage spreading for random Boolean and threshold networks under small external perturbations (damage), a problem which is relevant to many biological networks. We identify a new characteristic connectivity $K_s$, at which the average number of damaged nodes after a large number of dynamical updates is independent of the total number of nodes $N$. We estimate the critical connectivity for finite $N$ and show that it systematically deviates from the annealed approximation. Extending the approach followed in a previous study, we present new results indicating that internal dynamical correlations tend to increase not only the probability for small, but also for very large damage events, leading to a broad, fat-tailed distribution of damage sizes. These findings indicate that the descriptive and predictive value of averaged order parameters for finite size networks - even for biologically highly relevant sizes up to several thousand nodes - is limited.
dc.description4 pages, 4 figures. Accepted for the "Workshop on Computational Systems Biology", Leipzig 2008
dc.identifierhttps://arxiv.org/abs/0804.4498
dc.identifierhttp://arxiv.org/abs/0804.4498
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/159949
dc.subjectDisordered Systems and Neural Networks
dc.subjectCellular Automata and Lattice Gases
dc.subjectMolecular Networks
dc.titleWhen correlations matter - response of dynamical networks to small perturbations
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