Partitioning Biological Networks into Highly Connected Clusters with Maximum Edge Coverage

  • Falk Hüffner
  • Christian Komusiewicz
  • Adrian Liebtrau
  • Rolf Niedermeier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7875)


We introduce the combinatorial optimization problem Highly Connected Deletion, which asks for removing as few edges as possible from a graph such that the resulting graph consists of highly connected components. We show that Highly Connected Deletion is NP-hard and provide a fixed-parameter algorithm and a kernelization. We propose exact and heuristic solution strategies, based on polynomial-time data reduction rules and integer linear programming with column generation. The data reduction typically identifies 85 % of the edges that need to be deleted for an optimal solution; the column generation method can then optimally solve protein interaction networks with up to 5 000 vertices and 12 000 edges.


Column Generation Protein Interaction Network Annotation Term Large Connected Component Edge Deletion 
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 2013

Authors and Affiliations

  • Falk Hüffner
    • 1
  • Christian Komusiewicz
    • 1
  • Adrian Liebtrau
    • 2
  • Rolf Niedermeier
    • 1
  1. 1.Institut für Softwaretechnik und Theoretische InformatikTU BerlinGermany
  2. 2.Institut für InformatikFriedrich-Schiller-Universität JenaGermany

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