TY - JOUR

T1 - Approximation algorithms for orienting mixed graphs

AU - Elberfeld, Michael

AU - Segev, Danny

AU - Davidson, Colin R.

AU - Silverbush, Dana

AU - Sharan, Roded

N1 - Funding Information:
M.E. was supported by a research grant from the Dr. Alexander und Rita Besser-Stiftung. C.R.D. would like to thank Gerry Schwartz, Heather Reisman, and the University of Waterloo-Haifa International Experience Program for funding his visit to the University of Haifa, during which part of this work was done. R.S. was supported by a research grant from the Israel Science Foundation (grant no. 241/11).

PY - 2013/4/29

Y1 - 2013/4/29

N2 - 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.

AB - 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.

KW - Approximation algorithm

KW - Graph orientation

KW - Mixed graph

KW - Protein-protein interaction network

UR - http://www.scopus.com/inward/record.url?scp=84876408416&partnerID=8YFLogxK

U2 - 10.1016/j.tcs.2012.03.044

DO - 10.1016/j.tcs.2012.03.044

M3 - מאמר

AN - SCOPUS:84876408416

VL - 483

SP - 96

EP - 103

JO - Theoretical Computer Science

JF - Theoretical Computer Science

SN - 0304-3975

ER -