A closer look at the closest string and Closest Substring Problem

2011 Proceedings of the 13th Workshop on Algorithm Engineering and Experiments, ALENEX 2011

Volumn , Issue , 2011, Pages 13-24

  Chimani, Markus ^a   Woste, Matthias ^a   Böcker, Sebastian ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

Author keywords

Closest (sub)string problem; Experimental study; Integer linear program; Polyhedral study

Indexed keywords

HAMMING DISTANCE; INTEGER PROGRAMMING;

CLOSEST (SUB)STRING PROBLEM; CLOSEST STRING PROBLEMS; CLOSEST SUBSTRING PROBLEMS; COMPUTATIONAL BIOLOGY; DEGENERATE PRIMERS; EXPERIMENTAL STUDY; INTEGER LINEAR PROGRAMS; POLYHEDRAL STUDIES;

CONSTRAINT SATISFACTION PROBLEMS;

EID: 84861883184     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972917.2     Document Type: Conference Paper

References (29)

1. A. Andoni, P. Indyk, and M. Patrascu. On the optimality of the dimensionality reduction method. In Proc. FOCS 2006, pages 449-458. IEEE, 2006.
2. A. Ben-Dor, G. Lancia, R. Ravi, and J. Perone. Banishing bias from consensus sequences. In Proc. CPM 1997, volume 1264 of LNCS, pages 247-261. Springer, 1997.
3. S. Böcker, K. Jahn, J. Mixtacki, and J. Stoye. Computation of median gene clusters. Journal of Computational Biology, 16(8):1085-1099, 2009.
4. C. Boucher and J. King. Fast motif recognition via application of statistical thresholds. BMC Bioinformatics, 11 Suppl 1:S11, 2010.
5. J. Buhler and M. Tompa. Finding motifs using random projections. Journal of Computational Biology, 9(2):225-242, 2002.
6. Z.-Z. Chen, B. Ma, and L. Wang. A three-string approach to the closest string problem. In Proc. COCOON 2010, volume 6196 of LNCS, pages 449-458. Springer, 2010.
7. E. Danna, E. Rothberg, and C. Pape. Exploring relaxation induced neighborhoods to improve MIP solutions. Mathematical Programming, 102(1):71-90, 2005.
8. M. Das and H.-K. Dai. A survey of DNA motif finding algorithms. BMC Bioinformatics, 8(Suppl 7):S21, 2007.
9. J. Davila, S. Balla, and S. Rajasekaran. Fast and practical algorithms for planted (l, d) motif search. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4:544-552, 2007.
10. P. Evans, A. Smith, and H. Wareham. On the complexity of finding common approximate substrings. Theoretical Computer Science, 306(1-3):407-430, 2003.
11. S. Faro and E. Pappalardo. Ant-CSP: An ant colony optimization algorithm for the closest string problem. In Proc. SOFSEM 2010, volume 5901 of LNCS, pages 370-381. Springer, 2010.
12. M. Fischetti, F. Glover, and A. Lodi. The feasibility pump. Mathematical Programming, 104(1):91-104, 2005.
13. M. Frances and A. Litman. On covering problems of codes. Theory of Computing Systems, 30(2):113-119, 1997.
14. F. Gomes, C. Meneses, P. Pardalos, and G. Viana. A parallel multistart algorithm for the closest string problem. Computers & Operations Research, 35(11):36363643, 2008.
15. J. Gramm, R. Niedermeier, and P. Rossmanith. Fixedparameter algorithms for closest string and related problems. Algorithmica, 37(1):25-42, 2008.
16. F. Hufsky, L. Kuchenbecker, K. Jahn, J. Stoye, and S. Böcker. Swiftly computing center strings. In Proc. WABI 2010, volume 6293 of LNCS, pages 325-336. Springer, 2010.
17. T. Kelsey and L. Kotthoff. The exact closest string problem as a constraint satisfaction problem. CoRR, abs/1005.0089, 2010.
18. C. Kingsford, E. Zaslavsky, and M. Singh. A compact mathematical programming formulation for DNA motif finding. In Proc. CPM 2006, volume 4009 of LNCS, pages 233-245. Springer, 2006.
19. J. Lanctot, M. Li, B. Ma, S. Wang, and L. Zhang. Distinguishing string selection problems. In Proc. SODA 1999, pages 633-642. SIAM, 1999.
20. M. Li, B. Ma, and L. Wang. Finding similar regions in many strings. In Proc. STOC 1999, pages 473-482. ACM, 1999.
21. X. Liu, H. He, and O. Skora. Parallel genetic algorithm and parallel simulated annealing algorithm for the closest string problem. In Proc. ADMA 2005, volume 3584 of LNCS, pages 591-597. Springer, 2005.
22. B. Ma and X. Sun. More eficient algorithms for closest string and substring problems. In Proc. RECOMB 2008, pages 396-409. Springer, 2008.
23. D. Marx. The closest substring problem with small distances. In Proc. FOCS 2005, pages 63-72. IEEE, 10 2005.
24. M. McClure, T. Vasi, and W. Fitch. Comparative analysis of multiple protein-sequence alignment methods. Molecular Biology and Evolution, 11(4):571-592, 1994.
25. C. Meneses, Z. Lu, C. Oliveira, and P. Pardalos. Optimal solutions for the closest-string problem via integer programming. INFORMS Journal on Computing, 16(4):419-429, 2004.
26. C. Meneses, P. Pardalos, M. Resende, and A. Vazacopoulos. Modeling and solving string selection problems. In Proc. BIOMAT 2005, pages 54-64, 2006.
27. L. Wang and B. Zhu. Efficient algorithms for the closest string and distinguishing string selection problems. In Proc. FAW 2009, volume 5598 of LNCS, pages 261270. Springer, 2009.
28. Y. Wang, W. Chen, X. Li, and B. Cheng. Degenerated primer design to amplify the heavy chain variable region from immunoglobulin cDNA. BMC Bioinformatics, 7(Suppl 4):S9, 2006.
29. E. Zaslavsky and M. Singh. A combinatorial optimization approach for diverse motif finding applications. Algorithms for Molecular Biology, 1(1), 2006.