Improved orientations of physical networks

  • Authors:
  • Iftah Gamzu;Danny Segev;Roded Sharan

  • Affiliations:
  • Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel;Department of Statistics, University of Haifa, Haifa, Israel;Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel

  • Venue:
  • WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
  • Year:
  • 2010

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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(log n/ log log n), 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.