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Finding Exact and Maximum Occurrences of Protein Complexes in Protein-Protein Interaction Graphs

  • Guillaume Fertin
  • Romeo Rizzi
  • Stéphane Vialette
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3618)

Abstract

In the context of comparative analysis of protein-protein interaction graphs, we use a graph-based formalism to detect the preservation of a given protein complex G in the protein-protein interaction graph H of another species with respect to (w.r.t.) orthologous proteins. Two problems are considered: the Exact-(μ G , μ H )-Matching problem and the Max-(μ G , μ H ) problem, where μ G (resp. μ H ) denotes in both problems the maximum number of orthologous proteins in H (resp. G) of a protein in G (resp. H). Following [FLV04], the Exact-(μ G , μ H )-Matching problem asks for an injective homomorphism of G to H w.r.t. orthologous proteins. The optimization version is called the Max-(μ G , μ H )-Matching problem and is concerned with finding an injective mapping of a graph G to a graph H w.r.t. orthologous proteins that matches as many edges of G as possible. For both problems, the emphasis here is clearly on bounded degree graphs and extremal small values of parameters μ G and μ H .

Keywords

Bipartite Graph Injective Mapping Truth Assignment Orthologous Protein Injective Homomorphism 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Guillaume Fertin
    • 1
  • Romeo Rizzi
    • 2
  • Stéphane Vialette
    • 3
  1. 1.Laboratoire d’Informatique de Nantes-Atlantique (LINA), FRE CNRS 2729Université de NantesNantes Cedex 3France
  2. 2.Facoltà di Scienze – Dipartimento di Informatica e TelecomunicazioniUniversità degli Studi di TrentoPovo – TrentoItaly
  3. 3.Laboratoire de Recherche en Informatique (LRI), UMR CNRS 8623, Faculté des Sciences d’OrsayUniversité Paris-SudOrsayFrance

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