title: A comparison of algorithms for the pairwise alignment of biological networks.
abstract: BACKGROUND
  As biological inquiry produces ever more network data, such as protein-protein interaction networks, gene regulatory networks and metabolic networks, many algorithms have been proposed for the purpose of pairwise network alignment-finding a mapping from the nodes of one network to the nodes of another in such a way that the mapped nodes can be considered to correspond with respect to both their place in the network topology and their biological attributes. This technique is helpful in identifying previously undiscovered homologies between proteins of different species and revealing functionally similar subnetworks. In the past few years, a wealth of different aligners has been published, but few of them have been compared with one another, and no comprehensive review of these algorithms has yet appeared.
  
  
  RESULTS
  We present the problem of biological network alignment, provide a guide to existing alignment algorithms and comprehensively benchmark existing algorithms on both synthetic and real-world biological data, finding dramatic differences between existing algorithms in the quality of the alignments they produce. Additionally, we find that many of these tools are inconvenient to use in practice, and there remains a need for easy-to-use cross-platform tools for performing network alignment.
authors.affiliation: Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.
authors.forename: Connor
authors.initials: C
authors.lastname: Clark
authors.affiliation: Department of Computer Science, University of Colorado Colorado Springs, Colorado Springs, CO 80918, USA.
authors.forename: Jugal
authors.initials: J
authors.lastname: Kalita
mesh_terms: D000465:Algorithms; D000818:Animals; D006801:Humans; D025941:Protein Interaction Mapping / Q000379:methods*; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein