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

  • Authors:

  • Chung-Yuan Huang;Chia-Ying Cheng;Chuen-Tsai Sun

  • Affiliations:

  • Department of Computer Science and Information Engineering, Chang Gung University, 259 Wen Hwa 1st Road, Taoyuan 333, Taiwan and Research Center for Emerging Viral Infections, Chang Gung Universit ...;Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan;Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan

  • Venue:
  • Artificial Intelligence in Medicine
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

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.