TY - GEN
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 - 2011
Y1 - 2011
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 ordered source-target vertex pairs, it calls for assigning directions to the edges of the graph 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 the 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 algorithm to this problem. Our algorithm provides 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 ordered source-target vertex pairs, it calls for assigning directions to the edges of the graph 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 the 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 algorithm to this problem. Our algorithm provides 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=79960100533&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21458-5_35
DO - 10.1007/978-3-642-21458-5_35
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AN - SCOPUS:79960100533
SN - 9783642214578
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 416
EP - 428
BT - Combinatorial Pattern Matching - 22nd Annual Symposium, CPM 2011, Proceedings
Y2 - 27 June 2011 through 29 June 2011
ER -