Name
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.tcs.2012.03.044 | Theoretical Computer Science |
Keywords | DocType | Volume |
Protein–protein interaction network,Mixed graph,Graph orientation,Approximation algorithm | Journal | 483 |
ISSN | Citations | PageRank |
0304-3975 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Elberfeld | 1 | 115 | 10.63 |
| Danny Segev | 2 | 233 | 17.05 |
| Colin R. Davidson | 3 | 0 | 0.34 |
| Dana Silverbush | 4 | 11 | 2.42 |
| Roded Sharan | 5 | 2792 | 186.61 |