The SMAL web server: global multiple network alignment from pairwise alignments

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Motivation: Alignments of protein-protein interaction networks (PPIN) can be used to predict protein function, study conserved aspects of the interactome, and to establish evolutionary correspondences. Within this problem context, determining multiple network alignments (MNA) is a significant challenge that involves high computational complexity. A limited number of public MNA implementations are available currently and the majority of the pairwise network alignment (PNA) algorithms do not have MNA counterparts. Furthermore, current MNA algorithms do not allow choosing a specific PPIN relative to which an MNA could be constructed. Also, once an MNA is obtained, it cannot easily be modified, such as through addition of a new network, without expensive re-computation of the entire MNA.

Results: SMAL (Scaffold-Based Multiple Network Aligner) is a public, open-source, web-based application for determining MNAs from existing PNAs that addresses all the aforementioned challenges. With SMAL, PNAs can be combined rapidly to obtain an MNA. The software also supports visualization and user-data interactions to facilitate exploratory analysis and sensemaking. SMAL is especially useful when multiple alignments relative to a particular PPIN are required; furthermore, SMAL alignments are persistent in that existing correspondences between networks (obtained during PNA or MNA) are not lost as new networks are added. In comparative studies alongside existent MNA techniques, SMAL MNAs were found to be superior per a number of measures, such as the total number of identified homologs and interologs as well as the fraction of all identified correspondences that are functionally similar or homologous to the scaffold. While directed primarily at PPIN-alignment, SMAL is a generic network aligner and may be applied to arbitrary networks.

Availability information: The SMAL web server and source code is available at:

Supplementary information: Supplementary data are available at Bioinformatics online.

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