Liao Chung-Shou, Lu Kanghao, Baym Michael, Singh Rohit, Berger Bonnie
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Bioinformatics. 2009 Jun 15;25(12):i253-8. doi: 10.1093/bioinformatics/btp203.
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.
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.
Our software is available freely for non-commercial purposes on request from: http://isorank.csail.mit.edu/.
随着大型蛋白质-蛋白质相互作用网络的可得性不断增加，蛋白质网络比对问题正成为系统生物学的核心问题。网络比对进一步细分为两个子问题：局部比对，用于在网络中找到小的保守基序；全局比对，试图在两个网络的所有节点之间找到最佳映射。在本文中，我们的目标是改进现有的全局比对结果。更好的网络比对将尤其能够更准确地识别跨物种的功能直系同源物。
我们引入了IsoRankN（IsoRank-Nibble），一种基于成对比对分数诱导图上的谱聚类的全局多网络比对工具。在五个可用的真核生物网络的多重比对中，IsoRankN在覆盖范围和一致性方面优于现有的全局网络比对算法。基于谱方法，IsoRankN既容错又计算高效。
我们的软件可应要求免费用于非商业目的，网址为：http://isorank.csail.mit.edu/ 。
