fast and accurate alignment of protein interaction networks

Genome sequencing and large-scale interaction detection experiments are providing comprehensive lists of the proteins present in an organism and how they interact to create complex biological systems. To understand and interpret protein interaction networks, novel bioinformatics approaches are needed. Based on the success of sequence alignment in unveiling genome function, organization and evolution, alignment of protein interaction networks is expected to vastly increase our knowledge of biological processes, their evolution and adaptation to changing environmental conditions.

We developed a novel network alignment algorithm, called NetAligner, that features fast alignment of user-defined query pathways or protein complexes to whole species interactomes, as well as of interactome networks of different organisms for finding conserved complexes or higher-order assemblies. NetAligner is able to align networks of arbitrary topology and to accurately model evolutionary duplication events by respecting one-to-many and many-to-many homology relationships. In addition to considering interaction reliabilities to address potential false positives, NetAligner is the first network alignment algorithm that offers the option to predict likely conserved interactions to counter the high amount of false negatives in current interactomes, considerably increasing the performance of complex and pathway to interactome alignment. Moreover, NetAligner employs a fast method for assessing the statistical significance of alignment solutions, which serves to identify hits that are likely due to chance.

We currently provide complex to interactome, pathway to interactome and interactome to interactome alignment for all species combinations of H. sapiens, M. musculus, D. melanogaster, C. elegans, A. thaliana, S. Cerevisiae and E. coli. For each of those alignment tasks, the user can choose to either use the default parameters (determined based on a benchmark set of known conserved protein complexes and pathways between human, yeast and fly) or modify them to fulfill particular needs. All parameters are explained in detail on the Help page.

Please cite the following publications:

Pache RA, Céol A, Aloy P. NetAligner – A network alignment server to compare complexes, pathways and whole interactomes.
Nucleic Acids Res. 2012 PMID: 22618871

Pache RA, Aloy P. A Novel Framework for the Comparative Analysis of Biological Networks.
PLoS ONE. 2012 February;7(2):e31220. PMID: 22363585

Complex to interactome

Pathway to interactome

Interactome to interactome