2002/11/01 by B. Samuelsson, Björn Samuelsson, Samuelsson, B. +3
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Computational Drug Discovery Methods #Gene Regulatory Network Analysis #Receptor Mechanisms and Signaling #cond-mat.dis-nn #cond-mat.stat-mech
paper · pdf · doi:10.48550/arxiv.cond-mat/0211020
4 pages, 2 figures, to appear in Physical Review Letters. Version 3 changes: Made focus clearer, added ref to Socolar/Kauffman
arxiv created 2003/02/04 · arxiv updated 2009/11/30
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.