Improved Orientations of Physical Networks

  • Iftah Gamzu
  • Danny Segev
  • Roded Sharan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6293)


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(logn / loglogn), 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.


Input Graph Physical Network Optimal Orientation Oriented Edge Vertex Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Alon, N., Spencer, J.H.: The Probabilistic Method, 2nd edn. Wiley, Chichester (2000)CrossRefGoogle Scholar
  2. 2.
    Arkin, E.M., Hassin, R.: A note on orientations of mixed graphs. Discrete Applied Mathematics 116(3), 271–278 (2002)CrossRefGoogle Scholar
  3. 3.
    Even, G., Garg, N., Könemann, J., Ravi, R., Sinha, A.: Covering graphs using trees and stars. In: Arora, S., Jansen, K., Rolim, J.D.P., Sahai, A. (eds.) RANDOM 2003 and APPROX 2003. LNCS, vol. 2764, pp. 24–35. Springer, Heidelberg (2003)Google Scholar
  4. 4.
    Feige, U., Goemans, M.X.: Aproximating the value of two prover proof systems, with applications to MAX 2SAT and MAX DICUT. In: Proceedings 3rd Israel Symposium on Theory and Computing Systems, pp. 182–189 (1995)Google Scholar
  5. 5.
    Frederickson, G.N., Johnson, D.B.: Generating and searching sets induced by networks. In: de Bakker, J.W., van Leeuwen, J. (eds.) ICALP 1980. LNCS, vol. 85, pp. 221–233. Springer, Heidelberg (1980)CrossRefGoogle Scholar
  6. 6.
    Gamzu, I., Segev, D.: A sublogarithmic approximation for highway and tollbooth pricing. In: Proceedings of the 37th International Colloquium on Automata, Languages and Programming (to appear, 2010),
  7. 7.
    Goldschmidt, O., Hochbaum, D.S., Levin, A., Olinick, E.V.: The SONET edge-partition problem. Networks 41(1), 13–23 (2003)CrossRefGoogle Scholar
  8. 8.
    Hakimi, S.L., Schmeichel, E.F., Young, N.E.: Orienting graphs to optimize reachability. Information Processing Letters 63(5), 229–235 (1997)CrossRefGoogle Scholar
  9. 9.
    Hassin, R., Segev, D.: Robust subgraphs for trees and paths. ACM Transactions on Algorithms 2(2), 263–281 (2006)CrossRefGoogle Scholar
  10. 10.
    Håstad, J.: Some optimal inapproximability results. Journal of the ACM 48(4), 798–859 (2001)CrossRefGoogle Scholar
  11. 11.
    Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., Hirakawa, M.: KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Research 38(2), D355–D360 (2010)Google Scholar
  12. 12.
    Khot, S., Kindler, G., Mossel, E., O’Donnell, R.: Optimal inapproximability results for MAX-CUT and other 2-variable CSPs? SIAM Journal on Computing 37(1), 319–357 (2007)CrossRefGoogle Scholar
  13. 13.
    Lewin, M., Livnat, D., Zwick, U.: Improved rounding techniques for the MAX 2-SAT and MAX DI-CUT problems. In: Proceedings 9th International Conference on Integer Programming and Combinatorial Optimization, pp. 67–82 (2002)Google Scholar
  14. 14.
    Medvedovsky, A.: An algorithm for orienting graphs based on cause-effect pairs and its applications to orienting protein networks. Master’s thesis, Tel-Aviv University, Israel (2009)Google Scholar
  15. 15.
    Medvedovsky, A., Bafna, V., Zwick, U., Sharan, R.: An algorithm for orienting graphs based on cause-effect pairs and its applications to orienting protein networks. In: Crandall, K.A., Lagergren, J. (eds.) WABI 2008. LNCS (LNBI), vol. 5251, pp. 222–232. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Iftah Gamzu
    • 1
  • Danny Segev
    • 2
  • Roded Sharan
    • 1
  1. 1.Blavatnik School of Computer ScienceTel-Aviv UniversityTel-AvivIsrael
  2. 2.Department of StatisticsUniversity of HaifaHaifaIsrael

Personalised recommendations