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Fast and Accurate Alignment of Multiple Protein Networks

  • Maxim Kalaev
  • Vineet Bafna
  • Roded Sharan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4955)

Abstract

Comparative analysis of protein networks has proven to be a powerful approach for elucidating network structure and predicting protein function and interaction. A fundamental challenge for the successful application of this approach is to devise an efficient multiple network alignment algorithm. Here we present a novel framework for the problem. At the heart of the framework is a novel representation of multiple networks that is only linear in their size as opposed to current exponential representations. Our alignment algorithm is very efficient, being capable of aligning 10 networks with tens of thousands of proteins each in minutes. We show that our algorithm outperforms a previous strategy for the problem that is based on progressive alignment, and produces results that are more in line with current biological knowledge.

Keywords

Gene Ontology Accurate Alignment Network Alignment Progressive Alignment Alignment Graph 
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 2008

Authors and Affiliations

  • Maxim Kalaev
    • 1
  • Vineet Bafna
    • 2
  • Roded Sharan
    • 1
  1. 1.School of Computer ScienceTel Aviv UniversityTel AvivIsrael
  2. 2.CSEUniversity of California San DiegoUSA

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