Randomized Fixed-Parameter Algorithms for the Closest String Problem

Given a set S = { s 1 , s 2 , … , s n } of strings of equal length L and an integer d , the closest string problem (CSP) requires the computation of a string s of length L such that d ( s , s i ) ≤ d for each s i ∈ S , where d ( s , s i ) is the Hamming distance between s and s i . The problem is NP...

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Vydané v:Algorithmica Ročník 74; číslo 1; s. 466 - 484
Hlavní autori: Chen, Zhi-Zhong, Ma, Bin, Wang, Lusheng
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.01.2016
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Abstract Given a set S = { s 1 , s 2 , … , s n } of strings of equal length L and an integer d , the closest string problem (CSP) requires the computation of a string s of length L such that d ( s , s i ) ≤ d for each s i ∈ S , where d ( s , s i ) is the Hamming distance between s and s i . The problem is NP-hard and has been extensively studied in the context of approximation algorithms and fixed-parameter algorithms. Fixed-parameter algorithms provide the most practical solutions to its real-life applications in bioinformatics. In this paper we develop the first randomized fixed-parameter algorithms for CSP. Not only are the randomized algorithms much simpler than their deterministic counterparts, their time complexities are also significantly better than the previously best known (deterministic) algorithms.
AbstractList Given a set S = { s 1 , s 2 , … , s n } of strings of equal length L and an integer d , the closest string problem (CSP) requires the computation of a string s of length L such that d ( s , s i ) ≤ d for each s i ∈ S , where d ( s , s i ) is the Hamming distance between s and s i . The problem is NP-hard and has been extensively studied in the context of approximation algorithms and fixed-parameter algorithms. Fixed-parameter algorithms provide the most practical solutions to its real-life applications in bioinformatics. In this paper we develop the first randomized fixed-parameter algorithms for CSP. Not only are the randomized algorithms much simpler than their deterministic counterparts, their time complexities are also significantly better than the previously best known (deterministic) algorithms.
Author Ma, Bin
Chen, Zhi-Zhong
Wang, Lusheng
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  givenname: Bin
  surname: Ma
  fullname: Ma, Bin
  organization: School of Computer Science, University of Waterloo
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  fullname: Wang, Lusheng
  organization: Department of Computer Science, City University of Hong Kong
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Keywords Randomized algorithms
Fixed-parameter algorithms
The closest string problem
Computational biology
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References_xml – reference: DengXLiGLiZMaBWangLGenetic design of drugs without side-effectsSIAM J. Comput.2003324107310901029.68159200189810.1137/S0097539701397825
– reference: WangLDongLRandomized algorithms for motif detectionJ. Bioinform. Comput. Biol.20053510391052217037410.1142/S0219720005001508
– reference: Feng, Q., Wang, J., Li, S., Chen, J.: Random methods for parameterized problems. In: Proceedings of the 19th International Computing and Combinatorics Conference (COCOON), pp. 89–100 (2013)
– reference: Boucher, C., Brown, D.: Detecting motifs in a large data set: applying probabilistic insights to motif finding. In: Proceedings of the Conference on Bioinformatics and Computational Biology (BICoB), pp. 139–150 (2009)
– reference: Evans, P.A., Smith, A.D.: Complexity of approximating closest substring problems. In Proceedings of the 14th International Symposium on Foundations of Complexity Theory, pp. 210–221 (2003)
– reference: Böcker, S., Jahn, K., Mixtacki, J., Stoye, J.: Computation of median gene clusters. J. Comput. Biol. 16(8), 1085–1099 (2009)
– reference: LiMMaBWangLOn the closest string and substring problemsJ. ACM2002492157171214782110.1145/506147.506150
– reference: Ben-Dor, A., Lancia, G., Perone, J., Ravi, R.: Banishing bias from consensus sequences. In: Proceedings of the 8th Annual Symposium on Combinatorial Pattern Matching, pp. 247–261 (1997)
– reference: Chen, J., Lu, S., Sze, S.H., Zhang, F.: Improved algorithms for path, matching, and packing problems. In: Proceedings of the 17th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 298–307 (2007)
– reference: Gramm, J., Hüffner, F., Niedermeier, R.: Closest strings, primer design, and motif search. In: Florea, L. et al. (eds.) Currents in Computational Molecular Biology. Poster Abstracts of RECOMB 2002, pp. 74–75
– reference: Stojanovic, N., Berman, P., Gumucio, D., Hardison, R., Miller, W.: A linear-time algorithm for the 1-mismatch problem. In: Proceedings of the 5th International Workshop on Algorithms and Data Structures, pp. 126–135 (1997)
– reference: Zhao, R., Zhang, N.: A more efficient closest string algorithm. In: Proceedings of the 2nd International Conference on Bioinformatics and Computational Biology (2010)
– reference: DopazoJRodríguezASáizJCSobrinoFDesign of primers for PCR amplification of highly variable genomesCABIOS19939123125
– reference: Wang, L., Zhu, B.: Efficient algorithms for the closest string and distinguishing string selection problems. In: Proceedings of the 3rd International Frontiers of Algorithmics Workshop, pp. 261–270 (2009)
– reference: LucasKBuschMMösingerSThompsonJAAn improved microcomputer program for finding gene- or gene family-specific oligonucleotides suitable as primers for polymerase chain reactions or as probesCABIOS19917525529
– reference: Mauch, H., Melzer, M.J., Hu, J.S.: Genetic algorithm approach for the closest string problem. In: Proceedings of the 2nd IEEE Computer Society Bioinformatics Conference (CSB), pp. 560–561 (2003)
– reference: Davila, J., Balla, S., Rajasekaran, S.: Space and time efficient algorithms for planted motif search. In: Proceedings of the International Conference on Computational Science, pp. 822–829 (2006)
– reference: ChenZ-ZWangLFast exact algorithms for the closest string and substring problems with application to the planted (ℓ,d)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\ell , d)$$\end{document}-motif modelIEEE/ACM Trans. Comput. Biol. Bioinform.2011851400141010.1109/TCBB.2011.21
– reference: Marx, D., Razgon, I.: Fixed-parameter tractability of multicut parameterized by the size of the cutset. In: Proceedings of the 43rd Annual ACM Symposium on Theory of Computing (STOC), pp. 469–478 (2011)
– reference: MenesesCNLuZOliveiraCASPardalosPMOptimal solutions for the closest-string problem via integer programmingINFORMS J. Comput.2004164194291239.90077209832310.1287/ijoc.1040.0090
– reference: MarxDClosest substring problems with small distancesSIAM J. Comput.2008384138214101178.68695244845310.1137/060673898
– reference: FellowsMRGrammJNiedermeierROn the parameterized intractability of motif search problemsCombinatorica20062621411671109.68049222363210.1007/s00493-006-0011-4
– reference: Gramm, J., Guo, J., Niedermeier, R.: On exact and approximation algorithms for distinguishing substring selection. In: Proceedings of the 14th International Symposium on Foundations of Complexity Theory, pp. 159–209 (2003)
– reference: Jiao, Y., Xu, J., Li, M.: On the k-closest substring and k-consensus pattern problems. In: Proceedings of the 15th Annual Symposium on Combinatorial Pattern Matching, pp. 130–144 (2004)
– reference: MaBSunXMore efficient algorithms for closest string and substring problemsSIAM J. Comput.201039414321443255180810.1137/080739069
– reference: GrammJNiedermeierRRossmanithPFixed-parameter algorithms for closest string and related problemsAlgorithmica20033725421058.68119198461510.1007/s00453-003-1028-3
– reference: WangYChenWLiXChengBDegenerated primer design to amplify the heavy chain variable region from immunoglobulin cDNABMC Bioinform.20067Suppl. 4S910.1186/1471-2105-7-S4-S9
– reference: Nicolas, F., Rivals, E.: Complexities of the centre and median string problems. In: Proceedings of the 14th Annual Symposium on Combinatorial Pattern Matching, pp. 315–327 (2003)
– reference: ChenZ-ZMaBWangLA three-string approach to the closest string problemJ. Comput. Syst. Sci.2012781641781238.68190289635410.1016/j.jcss.2011.01.003
– reference: LanctotKLiMMaBWangSZhangLDistinguishing string search problemsInf. Comput.200318541551069.68116199474810.1016/S0890-5401(03)00057-9
– reference: Marx, D.: Randomized techniques for parameterized algorithms. In: Proceedings of the 7th International Symposium on Parameterized and Exact Computation (IPEC), p. 2 (2012)
– reference: ChenJLuSImproved parameterized set splitting algorithms: a probabilistic approachAlgorithmica200854447248910.1007/s00453-008-9206-y
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Snippet Given a set S = { s 1 , s 2 , … , s n } of strings of equal length L and an integer d , the closest string problem (CSP) requires the computation of a string s...
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SubjectTerms Algorithm Analysis and Problem Complexity
Algorithms
Computer Science
Computer Systems Organization and Communication Networks
Data Structures and Information Theory
Mathematics of Computing
Theory of Computation
Title Randomized Fixed-Parameter Algorithms for the Closest String Problem
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