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桥接与砖块网络基序:从复杂生物系统中识别重要构建模块

Bridge and brick network motifs: identifying significant building blocks from complex biological systems.

作者信息

Huang Chung-Yuan, Cheng Chia-Ying, Sun Chuen-Tsai

机构信息

Department of Computer Science and Information Engineering, Chang Gung University, 259 Wen Hwa 1st Road, Taoyuan 333, Taiwan.

出版信息

Artif Intell Med. 2007 Oct;41(2):117-27. doi: 10.1016/j.artmed.2007.07.006. Epub 2007 Sep 7.

Abstract

OBJECTIVE

A major focus in computational system biology research is defining organizing principles that govern complex biological network formation and evolution. The task is considered a major challenge because network behavior and function prediction requires the identification of functionally and statistically important motifs. Here we propose an algorithm for performing two tasks simultaneously: (a) detecting global statistical features and local connection structures in biological networks, and (b) locating functionally and statistically significant network motifs.

METHODS AND MATERIAL

Two gene regulation networks were tested: the bacteria Escherichia coli and the yeast eukaryote Saccharomyces cerevisiae. To understand their structural organizing principles and evolutionary mechanisms, we defined bridge motifs as composed of weak links only or of at least one weak link and multiple strong links, and defined brick motifs as composed of strong links only.

RESULTS

After examining functional and topological differences between bridge and brick motifs for predicting biological network behaviors and functions, we found that most genetic network motifs belong to the bridge category. This strongly suggests that the weak-tie links that provide unique paths for signal control significantly impact the signal processing function of transcription networks.

CONCLUSIONS

Bridge and brick motif content analysis can provide researchers with global and local views of individual real networks and help them locate functionally and topologically overlapping or isolated motifs for purposes of investigating biological system functions, behaviors, and similarities.

摘要

目的

计算系统生物学研究的一个主要重点是确定支配复杂生物网络形成和演化的组织原则。这项任务被认为是一项重大挑战,因为网络行为和功能预测需要识别功能上和统计学上重要的基序。在此,我们提出一种算法,可同时执行两项任务:(a)检测生物网络中的全局统计特征和局部连接结构,以及(b)定位功能上和统计学上显著的网络基序。

方法和材料

测试了两个基因调控网络:细菌大肠杆菌和酵母真核生物酿酒酵母。为了解它们的结构组织原则和进化机制,我们将桥接基序定义为由仅弱连接或至少一个弱连接和多个强连接组成,将砖块基序定义为由仅强连接组成。

结果

在研究桥接基序和砖块基序在预测生物网络行为和功能方面的功能和拓扑差异后,我们发现大多数遗传网络基序属于桥接类别。这强烈表明,为信号控制提供独特路径的弱连接显著影响转录网络的信号处理功能。

结论

桥接基序和砖块基序内容分析可为研究人员提供单个真实网络的全局和局部视图,并帮助他们定位功能上和拓扑上重叠或孤立的基序,以研究生物系统的功能、行为和相似性。

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