Journal Article

IsoRankN: spectral methods for global alignment of multiple protein networks

Chung-Shou Liao, Kanghao Lu, Michael Baym, Rohit Singh and Bonnie Berger

in Bioinformatics

Volume 25, issue 12, pages i253-i258
Published in print June 2009 | ISSN: 1367-4803
Published online May 2009 | e-ISSN: 1460-2059 | DOI:

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Motivation: 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.

Availability: Our software is available freely for non-commercial purposes on request from:


Journal Article.  4418 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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