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Improved Orientations of Physical Networks

  • Iftah Gamzu
  • Danny Segev
  • Roded Sharan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6293)

Abstract

The orientation of physical networks is a prime task in deciphering the signaling-regulatory circuitry of the cell. One manifestation of this computational task is as a maximum graph orientation problem, where given an undirected graph on n vertices and a collection of vertex pairs, the goal is to orient the edges of the graph so that a maximum number of pairs are connected by a directed path. We develop a novel approximation algorithm for this problem with a performance guarantee of O(logn / loglogn), improving on the current logarithmic approximation. In addition, motivated by interactions whose direction is pre-set, such as protein-DNA interactions, we extend our algorithm to handle mixed graphs, a major open problem posed by earlier work. In this setting, we show that a polylogarithmic approximation ratio is achievable under biologically-motivated assumptions on the sought paths.

Keywords

Input Graph Physical Network Optimal Orientation Oriented Edge Vertex Pair 
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 2010

Authors and Affiliations

  • Iftah Gamzu
    • 1
  • Danny Segev
    • 2
  • Roded Sharan
    • 1
  1. 1.Blavatnik School of Computer ScienceTel-Aviv UniversityTel-AvivIsrael
  2. 2.Department of StatisticsUniversity of HaifaHaifaIsrael

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