Approximation algorithms for orienting mixed graphs

Michael Elberfeld, Danny Segev, Colin R. Davidson, Dana Silverbush, Roded Sharan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Graph orientation is a fundamental problem in graph theory that has recently arisen in the study of signaling-regulatory pathways in protein networks. Given a graph and a list of source-target vertex pairs, one wishes to assign directions to the edges so as to maximize the number of pairs that admit a directed source-to-target path. When the input graph is undirected, a sub-logarithmic approximation is known for this problem. However, the approximability of the biologically-relevant variant, in which the input graph has both directed and undirected edges, was left open. Here we give the first approximation algorithms to this problem. Our algorithms provide a sub-linear guarantee in the general case, and logarithmic guarantees for structured instances.

Original languageEnglish
Pages (from-to)96-103
Number of pages8
JournalTheoretical Computer Science
Volume483
DOIs
StatePublished - 29 Apr 2013

Keywords

  • Approximation algorithm
  • Graph orientation
  • Mixed graph
  • Protein-protein interaction network

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