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Node handprinting: a scalable and accurate algorithm for aligning multiple biological networks
Citation
Radu, A and Charleston, M, Node handprinting: a scalable and accurate algorithm for aligning multiple biological networks, Journal of Computational Biology, 22, (7) pp. 687-697. ISSN 1066-5277 (2015) [Refereed Article]
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Copyright Statement
Copyright 2015 Mary Ann Liebert, Inc.
DOI: doi:10.1089/cmb.2014.0247
Abstract
Due to recent advancements in high-throughput sequencing technologies, progressively more
protein–protein interactions have been identified for a growing number of species. Subsequently,
the protein–protein interaction networks for these species have been further refined.
The increase in the quality and availability of these networks has in turn brought a demand for
efficient methods to analyze such networks. The pairwise alignment of these networks has been
moderately investigated,with numerous algorithms available, but there is very little progress in
the field of multiple network alignment. Multiple alignment of networks from different organisms
is ideal at finding abnormally conserved or disparate subnetworks. We present a fast
and accurate algorithmic approach, Node Handprinting (NH), based on our previous work with
Node Fingerprinting, which enables quick and accurate alignment of multiple networks. We
also propose two new metrics for the analysis of multiple alignments, as the current metrics are
not as sophisticated as their pairwise alignment counterparts. To assess the performance of NH,
we use previously aligned datasets as well as protein interaction networks generated from the
public database BioGRID. Our results indicate that NH compares favorably with current
methodologies and is the only algorithm capable of performing the more complex alignments.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | multiple network alignment, network alignment, network comparison, Protein– protein interaction networks |
| Research Division: | Biological Sciences |
| Research Group: | Biochemistry and cell biology |
| Research Field: | Systems biology |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding knowledge |
| Objective Field: | Expanding knowledge in the biological sciences |
| UTAS Author: | Charleston, M (Professor Michael Charleston) |
| ID Code: | 100236 |
| Year Published: | 2015 |
| Web of Science® Times Cited: | 3 |
| Deposited By: | Mathematics and Physics |
| Deposited On: | 2015-05-07 |
| Last Modified: | 2017-10-31 |
| Downloads: | 262 View Download Statistics |
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