Scaling in ordered and critical random boolean networks
Random Boolean networks, originally invented as models of genetic regulatory networks, are simple models for a broad class of complex systems that show rich dynamical structures. From a biological perspective, the most interesting networks lie at or near a critical point in parameter space that divi...
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| Veröffentlicht in: | Physical review letters 2003-02, Vol.90 (6), p.068702-068702, Article 068702 |
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| container_end_page | 068702 |
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| container_issue | 6 |
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| container_title | Physical review letters |
| container_volume | 90 |
| creator | Socolar, J E S Kauffman, S A |
| description | Random Boolean networks, originally invented as models of genetic regulatory networks, are simple models for a broad class of complex systems that show rich dynamical structures. From a biological perspective, the most interesting networks lie at or near a critical point in parameter space that divides "ordered" from "chaotic" attractor dynamics. We study the scaling of the average number of dynamically relevant nodes and the median number of distinct attractors in such networks. Our calculations indicate that the correct asymptotic scalings emerge only for very large systems. |
| doi_str_mv | 10.1103/physrevlett.90.068702 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 0031-9007 |
| ispartof | Physical review letters, 2003-02, Vol.90 (6), p.068702-068702, Article 068702 |
| issn | 0031-9007 1079-7114 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_73105763 |
| source | MEDLINE; American Physical Society Journals |
| subjects | Gene Expression Mathematical Computing Models, Genetic Nonlinear Dynamics |
| title | Scaling in ordered and critical random boolean networks |
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