IsoRankN: spectral methods for global alignment of multiple protein networks.
BACKGROUND
With the increasing availability of large protein-protein interaction networks, the question of protein network alignment is becoming central to systems biology. Network alignment is further delineated into two sub-problems: local alignment, to find small conserved motifs across networks, and global alignment, which attempts to find a best mapping between all nodes of the two networks. In this article, our aim is to improve upon existing global alignment results. Better network alignment will enable, among other things, more accurate identification of functional orthologs across species.


RESULTS
We introduce IsoRankN (IsoRank-Nibble) a global multiple-network alignment tool based on spectral clustering on the induced graph of pairwise alignment scores. IsoRankN outperforms existing algorithms for global network alignment in coverage and consistency on multiple alignments of the five available eukaryotic networks. Being based on spectral methods, IsoRankN is both error tolerant and computationally efficient.


BACKGROUND
Our software is available freely for non-commercial purposes on request from: http://isorank.csail.mit.edu/.
Liao
Chung-Shou
CS
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Lu
Kanghao
K
Baym
Michael
M
Singh
Rohit
R
Berger
Bonnie
B
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry*; D012984:Software; D049490:Systems Biology / Q000379:methods
D011506:Proteins