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网络基序:生物网络的最小研究单位

  • 陈长水;刘少飞
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  • 华南师范大学光子纳米生物技术研究中心,广州 510631

收稿日期: 2011-07-05

  修回日期: 2011-08-15

  网络出版日期: 2011-10-08

Network Motif: The Smallest Unit of a Biological Network

  • CHEN Changshui;LIU Shaofei
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  • Photon & Nano Research Centre for Biosciences, South China Normal University, Guangzhou 510631, China

Received date: 2011-07-05

  Revised date: 2011-08-15

  Online published: 2011-10-08

摘要

网络基序(network motif),是从生物网络中分解得到的最小研究单位,是构成生物网络的“砖块”,是系统生物学中最简单的研究对象。网络基序存在于各种生物网络中,具有信息处理的功能,通过理论和实验分析发现网络基序有重要的动力学功能。本文总结了网络基序的类型和功能研究方面的工作,包括转录网络中的基序(自我调节或者是反馈(负反馈(NAR)和正反馈(PAR)),正反馈环(FFL),单输入基序(SIM),多级输入基序(MIMs),链式调节子基序(Regulator Chain Motifs),多组分环基序(Multi-component Loop),桥基序和砖基序(Bridge and Brick motif)),信号转导网络中的基序和神经基序(神经元连接的样式),以及发掘和分析基序的数据库和工具。总结了基序的电路视角、进化以及对基序的反对意见,在应用方面,网络基序可能对合成生物学有重要的作用,最后对基序的研究工作提出了建议。网络基序可能是系统生物学的生物网络分析的初级形式,它为模块的分析和合成生物学提供了理论和实验的范本,网络基序需要用更多的网络,更多的在体实验分析,它的进一步发展可能会给生物网络理论带来重大的定则(principle)发现。

本文引用格式

陈长水;刘少飞 . 网络基序:生物网络的最小研究单位[J]. 科技导报, 2011 , 29(28) : 74 -74 . DOI: 10.3981/j.issn.1000-7857.2011.28.012

Abstract

The network motif (motif for short) is the smallest decomposable unit of a biological network or its smallest building block. It is an important research issue in systems biology. Motifs exist in various types of biological networks with information-processed functions. Simulations and experiments were carried out to study their dynamical properties. This paper reviews the styles and functions of motifs and the databases and tools to find motifs. The motifs we discuss in the paper include Negative Auto-Regulation(NAR), Positive Auto-Regulation (PAR), Forward Feedback Loop(FFL), Single Input Module(SIM), Multiple Input Modules (MIMs), regulator chain motifs, multi-component loop, bridge and brick motif in transcriptional networks, and motifs in signal transduction networks, as well as those in neural networks. The motifs might be viewed as the electric devices. This review also discusses the properties and the evolutions of network motifs, and related applications to synthetic biology. Finally, it is pointed out that the network motif study might be the first step in the studies of biological networks in systems biology to provide a good research method to study the module and synthetic biology. More types of motifs in various networks should be found out and more in-vivo experiments should be carried out. The further study might produce some general principles in biological networks.
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