title: Superpolynomial growth in the number of attractors in Kauffman networks.
abstract: The Kauffman model describes a particularly simple class of random Boolean networks. Despite the simplicity of the model, it exhibits complex behavior and has been suggested as a model for real world network problems. We introduce a novel approach to analyzing attractors in random Boolean networks, and applying it to Kauffman networks we prove that the average number of attractors grows faster than any power law with system size.
authors.affiliation: Complex Systems Division, Department of Theoretical Physics, Lund University, Sölvegatan 14A, S-223 62 Lund, Sweden. bjorn@thep.lu.se
authors.forename: Björn
authors.initials: B
authors.lastname: Samuelsson
authors.forename: Carl
authors.initials: C
authors.lastname: Troein
mesh_terms: D020407:Internet; D008962:Models, Theoretical; D011506:Proteins / Q000378:metabolism; D012944:Social Support
chemical_list: D011506:Proteins