title: Identification of functional modules from conserved ancestral protein-protein interactions.
abstract: BACKGROUND
  The increasing availability of large-scale protein-protein interaction (PPI) data has fueled the efforts to elucidate the building blocks and organization of cellular machinery. Previous studies have shown cross-species comparison to be an effective approach in uncovering functional modules in protein networks. This has in turn driven the research for new network alignment methods with a more solid grounding in network evolution models and better scalability, to allow multiple network comparison.
  
  
  RESULTS
  We develop a new framework for protein network alignment, based on reconstruction of an ancestral PPI network. The reconstruction algorithm is built upon a proposed model of protein network evolution, which takes into account phylogenetic history of the proteins and the evolution of their interactions. The application of our methodology to the PPI networks of yeast, worm and fly reveals that the most probable conserved ancestral interactions are often related to known protein complexes. By projecting the conserved ancestral interactions back onto the input networks we are able to identify the corresponding conserved protein modules in the considered species. In contrast to most of the previous methods, our algorithm is able to compare many networks simultaneously. The performed experiments demonstrate the ability of our method to uncover many functional modules with high specificity.
  
  
  BACKGROUND
  Information for obtaining software and supplementary results are available at http://bioputer.mimuw.edu.pl/papers/cappi.
authors.affiliation: Institute of Informatics, Warsaw University, Poland. januszd@mimuw.edu.pl
authors.forename: Janusz
authors.initials: J
authors.lastname: Dutkowski
authors.forename: Jerzy
authors.initials: J
authors.lastname: Tiuryn
mesh_terms: D005075:Biological Evolution; D003198:Computer Simulation; D017124:Conserved Sequence / Q000235:genetics*; D019143:Evolution, Molecular; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000737:chemistry* / Q000235:genetics*; D012689:Sequence Homology, Nucleic Acid; D015398:Signal Transduction / Q000502:physiology
chemical_list: D020543:Proteome