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Published Articles >> Table of Contents >> Abstract
Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05)
pp. 193-200
A Parallel Algorithm for Extracting Transcription Regulatory Network Motifs
Tie Wang, Arizona State University
Jeffrey W. Touchman, Arizona State University and Translational Genomics Research Institute
Weiyi Zhang, Arizona State University
Edward B. Suh, Translational Genomics Research Institute
Guoliang Xue, Arizona State University
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/BIBE.2005.8
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| Abstract |
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Network motifs have been demonstrated to be the
building blocks in many biological networks such as
transcriptional regulatory networks. Finding network
motifs plays a key role in understanding system level
functions and design principles of molecular interactions.
In this paper, we present a novel definition of
the neighborhood of a node. Based on this concept, we
formally define and present an effective algorithm for
finding network motifs. The method seeks a neighborhood
assignment for each node such that the induced
neighborhoods are partitioned with no overlap. We then
present a parallel algorithm to find network motifs using
a parallel cluster. The algorithm is applied on an
E. coli transcriptional regulatory network to find motifs
with size up to six. Compared with previous algorithms,
our algorithm performs better in terms of running time
and precision. Based on the motifs that are found in
the network, we further analyze the topology and coverage
of the motifs. The results suggest that a small
number of key motifs can form the motifs of a bigger
size. Also, some motifs exhibit a correlation with complex
functions. This study presents a framework for
detecting the most significant recurring subgraph patterns
in transcriptional regulatory networks.
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 Additional Information
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Index Terms- Network motifs, transcriptional regulatory network, systems biology
Citation:
Tie Wang, Jeffrey W. Touchman, Weiyi Zhang, Edward B. Suh, Guoliang Xue,
"A Parallel Algorithm for Extracting Transcription Regulatory Network Motifs,"
bibe,
pp. 193-200,
Fifth IEEE Symposium on Bioinformatics and Bioengineering (BIBE'05),
2005
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