title: PROPER: global protein interaction network alignment through percolation matching.
abstract: BACKGROUND
  The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PPI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging.
  
  
  RESULTS
  In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria.
  
  
  CONCLUSIONS
  We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch .
authors.affiliation: School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland. ehsan.kazemi@epfl.ch.
authors.forename: Ehsan
authors.identifier: http://orcid.org/0000-0001-8427-054X
authors.initials: E
authors.lastname: Kazemi
authors.affiliation: Department of Computer Science, ETHZ, Zurich, Switzerland.
authors.forename: Hamed
authors.initials: H
authors.lastname: Hassani
authors.affiliation: School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland.
authors.forename: Matthias
authors.initials: M
authors.lastname: Grossglauser
authors.affiliation: School of Life Sciences, EPFL, Lausanne, Switzerland.
authors.forename: Hassan
authors.initials: H
authors.lastname: Pezeshgi Modarres
mesh_terms: D000465:Algorithms; D000818:Animals; D006801:Humans; D051379:Mice; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps
keywords: Biological network; Global network alignment; Percolation graph matching; Protein-protein interaction