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Algorithmica

, Volume 61, Issue 2, pp 342–361 | Cite as

Approximation Algorithms for the Interval Constrained Coloring Problem

  • Ernst Althaus
  • Stefan Canzar
  • Khaled Elbassioni
  • Andreas Karrenbauer
  • Julián Mestre
Article

Abstract

We consider the interval constrained coloring problem, which appears in the interpretation of experimental data in biochemistry. Monitoring hydrogen-deuterium exchange rates via mass spectroscopy experiments is a method used to obtain information about protein tertiary structure. The output of these experiments provides data about the exchange rate of residues in overlapping segments of the protein backbone. These segments must be re-assembled in order to obtain a global picture of the protein structure. The interval constrained coloring problem is the mathematical abstraction of this re-assembly process.

The objective of the interval constrained coloring problem is to assign a color (exchange rate) to a set of integers (protein residues) such that a set of constraints is satisfied. Each constraint is made up of a closed interval (protein segment) and requirements on the number of elements that belong to each color class (exchange rates observed in the experiments).

We show that the problem is NP-complete for arbitrary number of colors and we provide algorithms that given a feasible instance find a coloring that satisfies all the coloring requirements within ±1 of the prescribed value. In light of our first result, this is essentially the best one can hope for. Our approach is based on polyhedral theory and randomized rounding techniques. Furthermore, we consider a variant of the problem where we are asked to find a coloring satisfying as many fragments as possible. If we relax the coloring requirements by a small factor of (1+ε), we propose an algorithm that finds a coloring “satisfying” this maximum number of fragments and that runs in quasi-polynomial time if the number of colors is polylogarithmic.

Keywords

Approximation algorithms Coloring problems LP rounding 

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References

  1. 1.
    Althaus, E., Canzar, S., Emmett, M.R., Karrenbauer, A., Marshall, A.G., Meyer-Basese, A., Zhang, H.: Computing H/D-exchange speeds of single residues from data of peptic fragments. In: Proceedings of the 23rd Annual ACM Symposium on Applied Computing, pp. 1273–1277 (2008) Google Scholar
  2. 2.
    Komusiewicz, C., Niedermeier, R., Uhlmann, J.: Deconstructing intractability: a case study for interval constrained coloring. In: Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching, pp. 207–220 (2009) Google Scholar
  3. 3.
    Chang, J., Erlebach, T., Gailis, R., Khuller, S.: Broadcast scheduling: algorithms and complexity. In: Proceedings of the 19th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 473–482 (2008) Google Scholar
  4. 4.
    Gandhi, R., Khuller, S., Parthasarathy, S., Srinivasan, A.: Dependent rounding and its applications to approximation algorithms. J. ACM 53(3), 324–360 (2006) MathSciNetCrossRefGoogle Scholar
  5. 5.
    Schrijver, A.: Combinatorial Optimization—Polyhedra and Efficiency. Algorithms and Combinatorics, vol. 24. Springer, Berlin (2003) zbMATHGoogle Scholar
  6. 6.
    Uno, T.: A fast algorithm for enumerating bipartite perfect matchings. In: Proceedings of the 12th International Conference Algorithms and Computation, pp. 367–379 (2001) Google Scholar
  7. 7.
    Elbassioni, K.M., Sitters, R., Zhang, Y.: A quasi-PTAS for profit-maximizing pricing on line graphs. In: Proceedings of the 15th Annual European Symposium on Algorithms, pp. 451–462 (2007) Google Scholar
  8. 8.
    Canzar, S.: Lagrangian relaxation—solving NP-hard problems in computational biology via combinatorial optimization. PhD thesis, Universität des Saarlandes (2008) Google Scholar
  9. 9.
    Garey, M.R., Johnson, D.S.: Computers and Intractability, a Guide to the Theory of NP-Completeness. Freeman, New York (1979) zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Ernst Althaus
    • 1
  • Stefan Canzar
    • 2
  • Khaled Elbassioni
    • 3
  • Andreas Karrenbauer
    • 4
  • Julián Mestre
    • 3
  1. 1.Johannes Gutenberg-UniversitätMainzGermany
  2. 2.Centrum Wiskunde & InformaticaAmsterdamThe Netherlands
  3. 3.Max-Planck-Institut für InformatikSaarbrückenGermany
  4. 4.Institute of MathematicsEPFLLausanneSwitzerland

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