Bridge and brick network motifs: identifying significant building blocks from complex biological systems.
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
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.
Huang
Chung-Yuan
CY
Department of Computer Science and Information Engineering, Chang Gung University, 259 Wen Hwa 1st Road, Taoyuan 333, Taiwan. gscott@mail.cgu.edu.tw
Cheng
Chia-Ying
CY
Sun
Chuen-Tsai
CT
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005786:Gene Expression Regulation / Q000235:genetics; D053263:Gene Regulatory Networks / Q000235:genetics*; D016571:Neural Networks, Computer; D015398:Signal Transduction / Q000235:genetics; D012984:Software; D049490:Systems Biology / Q000379:methods*; D014158:Transcription, Genetic / Q000235:genetics