標題: Bridge and brick network motifs: Identifying significant building blocks from complex biological systems
作者: Huang, Chung-Yuan
Cheng, Chia-Ying
Sun, Chuen-Tsai
資訊工程學系
Department of Computer Science
關鍵字: small-world properties;local clustering;strong/weak-tie link;network-oriented approach;complex biological systems;network motif
公開日期: 1-Oct-2007
摘要: 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 biotogical system functions, behaviors, and similarities. (C) 2007 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.artmed.2007.07.006
http://hdl.handle.net/11536/10262
ISSN: 0933-3657
DOI: 10.1016/j.artmed.2007.07.006
期刊: ARTIFICIAL INTELLIGENCE IN MEDICINE
Volume: 41
Issue: 2
起始頁: 117
結束頁: 127
Appears in Collections:Articles


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