A niching genetic k-means algorithm and its applications to gene expression data

Soft Computing

Volumn 14, Issue 1, 2010, Pages 9-19

  Sheng, Weiguo ^a   Tucker, Allan ^a   Liu, Xiaohui ^a  

^a BRUNEL UNIVERSITY   (United Kingdom)

Author keywords

Clustering; Gene expression; Genetic algorithms; K means; Niching methods

Indexed keywords

CLUSTERING; CLUSTERING METHODS; CLUSTERING SOLUTIONS; CRITERION FUNCTIONS; EVOLUTIONARY CLUSTERING; GENE EXPRESSION DATA; GENETIC K-MEANS ALGORITHM; HIGH-QUALITY SOLUTIONS; K-MEANS; NICHING GENETIC ALGORITHM; NICHING METHODS; ONE STEP; PARTITIONAL CLUSTERING; PREMATURE CONVERGENCE; SIMULATED DATA; SUM OF SQUARED ERRORS;

BIOACTIVITY; CLUSTER ANALYSIS; COMPUTATIONAL EFFICIENCY; CONVERGENCE OF NUMERICAL METHODS; GENE EXPRESSION; GENETIC ALGORITHMS;

CLUSTERING ALGORITHMS;

EID: 69249221444     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-008-0386-9     Document Type: Article

References (46)

1. Areibi S, Yang Z (2004) Effective memetic algorithms for VLSI design automation = genetic algorithms + local search + multi-level clustering. Evolut Comput 12(3):327-353
2. Babu GP, Murty MN (1994) Clustering with evolution strategies. Pattern Recogn 27(2):321-329
3. Back T (1996) Evolutionary algorithms in theory and practice. Oxford University Press, Oxford
4. Beasley D, Bull DR, Martin RR (1993) A sequential niche technique for multimodal function optimization. Evolut Comput 1(2):101-125
5. Bezdek JC (1981) Pattern recognition with fuzzy objective functions. Plenum, New York
6. Branke J, Middendorf M, Schneider F (1998) Improved heuristics and a genetic algorithm for finding short supersequences. Oper Res 20(1):39-45
7. Brown DE, Huntley CL (1992) A practical application of simulated annealing to clustering. Pattern Recogn 25(4):401-412
8. Cho RJ, Campbell MJ, Winzeler EA, Steinmetz L, Conway A, Wodicka L, Wolfsberg TG, Gabrieflian AE, Landsman D, Lockhart DJ, Davis RW (1998) A genome-wide transcriptional analysis of the mitotic cell cycle. Molec Cell 2(1):65-73
9. Cucchiara R (1998) Genetic algorithms for clustering in machine vision. Mach Vis Appl 11(1):1-6
10. Damavandi N, Safavi-Naeini S (2003) A global optimization algorithm based on combined evolutionary programming for cluster analysis. In: Proceedings of IEEE conference on electrical and computer engineering, vol 2, pp 4-7
11. DeJong KA (1975) An analysis of the behavior of a class of genetic adaptive systems. PhD dissertation, University of Michigan, Ann Arbor
12. Dembele D, Kastner P (2003) Fuzzy c-means method for clustering microarray data. Bioinformatics 19(8):973-980
13. Duda RO, Hart PE (1973) Pattern classification and scene analysis. Wiley, New York
14. Duda RO, Hart PE, Stork DG (2001) Pattern classification, 2nd edn. Wiley, New York
15. Frey B, Dueck D (2007) Clustering by passing messages between data points. Science 315:972-976
16. Garey M, Johnson D (1979) Computers and intractability - a guide to the theory of NP-completeness. W.H. Freeman, San Francisco
17. Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading
18. Goldberg DE, Richardson J (1987) Genetic algorithms with sharing for multimodal function optimization. In: Proceedings of the 2nd international conference on genetic algorithms, Hillsdale, New Jersey, USA, pp 41-49
19. Hall LO, Ozyurt B, Bezdek JC (1999) Clustering with a genetically optimized approach. IEEE Trans Evol Comput 3(2):103-112
20. Hartigan JA, Wong MA (1979) A k-means clustering algorithm. Appl Stat 28:100-110
21. Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor
22. Iyer VR, Eisen MB, Ross DT, Schuler G, Moore T, Lee JC, Trent JM, Staudt LM, Hudson J Jr, Boguski MS, Lashkari D, Shalon D, Botstein D, Brown PO (1999) The transcriptional program in the response of human fibroblasts to serum. Science 283:83-87
23. Jain AK, Dubes RC (1988) Algorithms for clustering data. Prentice Hall, Englewood Cliffs
24. Jin HD, Leung KS, Leung WM (2001) Genetic-guided model-based clustering algorithms. Proc Int Conf Artif Intell 2:653-659
25. Klein RW, Dubes RC (1989) Experiments in projection and clustering by simulated annealing. Pattern Recogn 22(2):213-220
26. Kodek DM (1980) Design of optimal finite word length FIR digital filters using integer programming techniques. IEEE Trans ASSP 28:304-308
27. Koontz WL, Narendra PM, Fukunaga K (1975) A branch and bound clustering algorithm. IEEE Trans Comp 24:908-915
28. Krishna K, Murty MN (1999) Genetic k-means algorithm. IEEE Trans Syst Man Cybern B Cybern 29(3):433-439
29. Lozano JA, Larrañaga P (1999) Applying genetic algorithms to search for the best hierarchical clustering of a dataset. Pattern Recogn Lett 20(9):911-918
30. Li FF, Morgan R, Williams D (1997) Hybrid genetic approaches to ramping rate constrained dynamic economic dispatch. Electric Power Syst Res 43(2):97-103
31. Mahfoud SW (1995) Niching methods for genetic algorithms. PhD dissertation, Univ. of Illinois, Urbana-Champaign
32. Maulik U, Bandyopadhyay S (2000) Genetic algorithm-based clustering technique. Pattern Recogn 33:1455-1465
33. Michalewicz Z (1996) Genetic algorithms + Data structure = Evolution programs, 3rd edn. Springer, Berlin
34. Murthy CA, Chowdhury N (1996) In search of optimal clusters using genetic algorithms. Pattern Recogn Lett 17:825-832
35. Pelikan M, Goldberg DE (2000) Genetic algorithm clustering, and the breaking of symmetry. In: Proceedings of parallel problem solving from nature, pp 385-394
36. Petrowski A (1996) A clearing procedure as a niching method for genetic algorithms. In: Proceedings of IEEE international conference on evolutionary computation, pp 798-803
37. Sareni B, Krähenbühl L (1998) Fitness sharing and niching methods revisited. IEEE Trans Evol Comput 2:97-106
38. Sareni B, Krahenbuhl L, Nicolas A (2000) Efficient genetic algorithms for solving hard constrained optimization problems. IEEE Trans Magn 36(4):1027-1030
39. Sarkar M, Yegnanarayana B, Khemani D (1997) A clustering algorithm using an evolutionary programming-based approach. Pattern Recogn Lett 18:975-986
40. Sharan R, Shamir R (2000) CLICK: A clustering algorithm with application to gene expression analysis. In: Proceedings of AAAI-ISMB, pp 307-316
41. Tamburino LA, Zmuda MA, Rizki MM (1995) Generating pattern recognition systems using evolutionary learning expert. IEEE Intell Syst 10(4):63-68
42. Tavazoie S, Hughes D, Campbell JMJ, Cho RJ, Church GM (1999) Systematic determination of genetic network architecture. Nat Genetic 22:281-285
43. Villarreal B, Karwan MH (1982) Multicriteria dynamic programming with an application to the integer case. J Math Anal Appl 38:43-69
44. Whitley D (1995) Modeling hybrid genetic algorithms. In: Winter G, Periaux J, Galan M, Cuesta P (eds) Genetic algorithms in engineering and computer science. Wiley, New York, pp 191-201
45. Wu S, Liew AWC, Yan H, Yang M (2004) Cluster analysis of gene expression database on self-splitting and merging competitive learning. IEEE Trans Inf Technol Biomed 8(1):5-15
46. Yeung KY (2000) Clustering analysis of gene expression data. PhD Thesis, University of Washington