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摘要翻译：
各种物理、社会和生物系统在多个时间尺度上产生相互关联的复杂波动。在生理系统中，这些长期的相关性随着疾病和衰老而改变。生命系统中的这种相关波动被归因于多个控制系统的相互作用；然而，这种行为背后的机制仍然未知。在这里，我们证明了许多不同类型的动力学行为，包括以其功率谱的$1/f$-标度为特征的相关涨落，可以在简单信令单元的网络中出现。我们发现，在一般条件下，满足两个要求的系统可以产生复杂的动力学：i）一个“小世界”拓扑和ii）存在噪声。我们的发现支持两个值得注意的结论：第一，复杂的类似生理的信号可以用最小的组件集建模；第二，满足条件(i)和(ii)的系统对某种程度的退化是鲁棒的，即它们仍然能够产生$1/f$-动力学。
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英文标题：
《Emergence of Complex Dynamics in a Simple Model of Signaling Networks》
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作者：
Luis A.N. Amaral (1), Albert Diaz-Guilera (1,2,3), Andre A. Moreira
(1), Ary L. Goldberger (2), Lewis A. Lipsitz (4) ((1) Department of Chemical
and Biological Engineering, Northwestern University (2) Cardiovascular
Division, Beth Israel Deaconess Medical Center, Harvard Medical School (3)
Dept. Fisica Fonamental, Universitat de Barcelona (4) Hebrew Rehabilitation
Center for the Aged, Harvard Medical School)
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最新提交年份：
2004
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Physics 物理学
二级分类：Soft Condensed Matter 软凝聚态物质
分类描述：Membranes, polymers, liquid crystals, glasses, colloids, granular matter
膜，聚合物，液晶，玻璃，胶体，颗粒物质
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一级分类：Physics 物理学
二级分类：Biological Physics 生物物理学
分类描述：Molecular biophysics, cellular biophysics, neurological biophysics, membrane biophysics, single-molecule biophysics, ecological biophysics, quantum phenomena in biological systems (quantum biophysics), theoretical biophysics, molecular dynamics/modeling and simulation, game theory, biomechanics, bioinformatics, microorganisms, virology, evolution, biophysical methods.
分子生物物理、细胞生物物理、神经生物物理、膜生物物理、单分子生物物理、生态生物物理、生物系统中的量子现象（量子生物物理）、理论生物物理、分子动力学/建模与模拟、博弈论、生物力学、生物信息学、微生物、病毒学、进化论、生物物理方法。
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英文摘要：
A variety of physical, social and biological systems generate complex fluctuations with correlations across multiple time scales. In physiologic systems, these long-range correlations are altered with disease and aging. Such correlated fluctuations in living systems have been attributed to the interaction of multiple control systems; however, the mechanisms underlying this behavior remain unknown. Here, we show that a number of distinct classes of dynamical behaviors, including correlated fluctuations characterized by $1/f$-scaling of their power spectra, can emerge in networks of simple signaling units. We find that under general conditions, complex dynamics can be generated by systems fulfilling two requirements: i) a ``small-world'' topology and ii) the presence of noise. Our findings support two notable conclusions: first, complex physiologic-like signals can be modeled with a minimal set of components; and second, systems fulfilling conditions (i) and (ii) are robust to some degree of degradation, i.e., they will still be able to generate $1/f$-dynamics.
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PDF链接：
https://arxiv.org/pdf/q-bio/0411039
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