人工进化和生物网络的模体统计
Motif statistics of artificially evolved and biological networks
摘要:
通过选择短动态吸引子进化的模型种群,可以成功地再现基因调控网络的拓扑特征。网络的进化群体表现出模体统计,由显著性概况总结,其与{ \it E. coli、S. cerevsiae}和{ \it B. subtilis},在诸如线性基元和前馈回路的过量以及反馈回路的不足等特征中。缓慢松弛到停滞状态是崎岖的适应度景观的标志,独立进化的种群探索在网络属性上强烈不同的不同山谷。
英文摘要:
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.
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