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生态学与进化中的网络思维。

Network thinking in ecology and evolution.

作者信息

Proulx Stephen R, Promislow Daniel E L, Phillips Patrick C

机构信息

Center for Ecology and Evolutionary Biology, 5289 University of Oregon, Eugene, OR 97403-5289, USA.

出版信息

Trends Ecol Evol. 2005 Jun;20(6):345-53. doi: 10.1016/j.tree.2005.04.004.

Abstract

Although pairwise interactions have always had a key role in ecology and evolutionary biology, the recent increase in the amount and availability of biological data has placed a new focus on the complex networks embedded in biological systems. The increased availability of computational tools to store and retrieve biological data has facilitated wide access to these data, not just by biologists but also by specialists from the social sciences, computer science, physics and mathematics. This fusion of interests has led to a burst of research on the properties and consequences of network structure in biological systems. Although traditional measures of network structure and function have started us off on the right foot, an important next step is to create biologically realistic models of network formation, evolution, and function. Here, we review recent applications of network thinking to the evolution of networks at the gene and protein level and to the dynamics and stability of communities. These studies have provided new insights into the organization and function of biological systems by applying existing techniques of network analysis. The current challenge is to recognize the commonalities in evolutionary and ecological applications of network thinking to create a predictive science of biological networks.

摘要

尽管成对相互作用在生态学和进化生物学中一直起着关键作用,但近期生物数据量及其可获取性的增加,使人们将新的重点放在了生物系统中所嵌入的复杂网络上。用于存储和检索生物数据的计算工具的可用性提高,不仅方便了生物学家,也方便了社会科学、计算机科学、物理学和数学领域的专家广泛获取这些数据。这种兴趣的融合引发了对生物系统中网络结构的特性和后果的大量研究。尽管传统的网络结构和功能测量方法为我们开了个好头,但重要的下一步是创建关于网络形成、进化和功能的生物学现实模型。在此,我们回顾网络思维在基因和蛋白质水平的网络进化以及群落动态和稳定性方面的近期应用。这些研究通过应用现有的网络分析技术,为生物系统的组织和功能提供了新的见解。当前的挑战是认识到网络思维在进化和生态应用中的共性,以创建一门生物网络的预测科学。

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