Motif statistics of artificially evolved and biological networks - Danacı, Burçin; Anıl, Mehmet Ali; Erzan, Ayşe (American Physical Society (APS), 2014)
Topological features of gene regulatory networks can be successfully reproduced by a model population evolving under selection for short dynamical attractors. The evolved population of networks exhibit motif statistics, summarized by significance profiles, which closely match those of {\it E. coli, S. cerevsiae} and {\it B. subtilis}, in such features as the excess of linear motifs and feed-forward loops, and deficiency of feedback loops. The slow relaxation to stasis is a hallmark of a rugged fitness landscape, with independently evolving populations exploring distinct valleys strongly differing in network properties.

7 pages, 9 figures to be published in Physical Review E
Keywords: Models, Statistical; Bacteria; Molecular Networks (q-bio.MN); Models, Biological; Bacterial Proteins; Gene Expression Regulation; Biomimetics; FOS: Biological sciences; Quantitative Biology - Molecular Networks; Computer Simulation; Gene Regulatory Networks; Signal Transduction