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Dynamics of random Boolean networks.

University of Calgary (Canada).

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Dynamics of random Boolean networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dynamics of random Boolean networks./
作者:	Berdahl, Andrew Macdonald.
面頁冊數:	129 p.
附註:	Source: Masters Abstracts International, Volume: 48-01, page: .
Contained By:	Masters Abstracts International48-01.
標題:	Biology, Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR51091
ISBN:	9780494510919

Dynamics of random Boolean networks.
Berdahl, Andrew Macdonald.

Dynamics of random Boolean networks. - 129 p.

Source: Masters Abstracts International, Volume: 48-01, page: .

Thesis (M.Sc.)--University of Calgary (Canada), 2009.

Random Boolean networks are conceptual models for systems of interacting elements. The dynamics of these models can be represented by a directed state space network by linking each dynamical state, represented as a node, to its temporal successor. Like all finite discrete deterministic systems the dynamics must eventually settle into a periodic attractor cycle. In this thesis we clarify how different weighting schemes and sampling methods affect the estimates for attractor length distributions in random Boolean networks. We find that the unbiased distribution of attractor lengths decays as a power-law for all K > 1, thus power-law behaviour in this distribution is not an indicator of criticality. However, we observe a power-law in the distribution of the sizes of "avalanches" in critical random Boolean networks only. Finally, we find that dynamical criticality manifests itself as multi-scale heterogeneity in the state space networks.

ISBN: 9780494510919Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Dynamics of random Boolean networks.
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520 $a Random Boolean networks are conceptual models for systems of interacting elements. The dynamics of these models can be represented by a directed state space network by linking each dynamical state, represented as a node, to its temporal successor. Like all finite discrete deterministic systems the dynamics must eventually settle into a periodic attractor cycle. In this thesis we clarify how different weighting schemes and sampling methods affect the estimates for attractor length distributions in random Boolean networks. We find that the unbiased distribution of attractor lengths decays as a power-law for all K > 1, thus power-law behaviour in this distribution is not an indicator of criticality. However, we observe a power-law in the distribution of the sizes of "avalanches" in critical random Boolean networks only. Finally, we find that dynamical criticality manifests itself as multi-scale heterogeneity in the state space networks.
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