Unsupervised clustering in mRNA expression profiles

Computers in Biology and Medicine

Volumn 36, Issue 10, 2006, Pages 1126-1142

  Tasoulis, D K ^a   Plagianakos, V P ^a   Vrahatis, M N ^a  

^a UNIVERSITY OF PATRAS   (Greece)

Author keywords

Bioinformatics; Cluster analysis; Dimension reduction; Gene expression analysis; k windows algorithm; mRNA expression profiles; Unsupervised clustering

Indexed keywords

BIOINFORMATICS; CLUSTERING ALGORITHM; DIMENSION REDUCTION; GENE EXPRESSION ANALYSIS; MRNA EXPRESSION PROFILES; UNSUPERVISED CLUSTERING;

ALGORITHMS; BIOMEDICAL ENGINEERING; DATA REDUCTION; GENES; GENETIC ENGINEERING;

RNA;

MESSENGER RNA;

ALGORITHM; ARTICLE; GENE CLUSTER; GENE EXPRESSION; HUMAN; MAJOR CLINICAL STUDY; MICROARRAY ANALYSIS; PRIORITY JOURNAL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COLONIC NEOPLASMS; FEMALE; GENE EXPRESSION PROFILING; HUMANS; LEUKEMIA, LYMPHOCYTIC, ACUTE; LEUKEMIA, MYELOCYTIC, ACUTE; LEUKEMIA, MYELOID, ACUTE; LYMPHOMA; MALE; MATHEMATICAL COMPUTING; NEOPLASMS; NEURAL NETWORKS (COMPUTER); OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PRECURSOR CELL LYMPHOBLASTIC LEUKEMIA-LYMPHOMA; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; RNA, MESSENGER; SOFTWARE;

EID: 33746732174     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2005.09.003     Document Type: Article

References (52)

1. D. Jiang, C. Tang, A. Zhangi, Cluster analysis for gene expression data: a survey. IEEE Trans. Knowledge Data Eng. 16 (11) (2004) 1370-1386.
2. Eisen M.B., Spellman P.T., Brown P.O., and Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95 (1998) 14863-14868
3. Wen X., Fuhrman S., Michaels G., Carr D., Smith S., Barker J., and Somogyi R. Large-scale temporal gene expression mapping of cns development. Proc. Natl. Acad. Sci. USA 95 (1998) 334-339
4. Golub T.R., Slomin D.K., Tamayo P., Huard C., Gaasenbeek M., Mesirov J., Coller H., Loh M.L., Downing J., Caligiuri M., Bloomfield C., and Lander E. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286 (1999) 531-537
5. Bellman R. Adaptive Control Processes: A Guided Tour (1961), Princeton University Press, Princeton
6. Hastie T., Tibshirani R., and Friedman J. The Elements of Statistical Learning (2001), Springer, Berlin
7. Fayyad U.M., Piatetsky-Shapiro G., and Smyth P. Advances in Knowledge Discovery and Data Mining (1996), MIT Press, Cambridge
8. M.S. Aldenderfer, R.K. Blashfield, Cluster Analysis, Quantitative Applications in the Social Sciences, vol. 44, SAGE Publications, London, 1984.
9. Ramasubramanian V., and Paliwal K. Fast k-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding. IEEE Trans. Signal Process. 40 3 (1992) 518-531
10. R.W. Becker, G.V. Lago, A global optimization algorithm, in: Proceedings of the Eighth Allerton Conference on Circuits and Systems Theory, 1970, pp. 3-12.
11. Törn A., and Žilinskas A. Global Optimization (1989), Springer, Berlin
12. Alon U., Barkai N., Notterman D.A., Gish K., Ybarra S., Mack D., and Levine A.J. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide array. Proc. Natl. Acad. Sci. USA 96 12 (1999) 6745-6750
13. Shamir R., and Sharan R. CLICK: a clustering algorithm for gene expression analysis. Eighth International Conference on Intelligent Systems for Molecular Biology (ISMB 00) (2000), AAAIPress
14. Tang C., Zhang A., and Ramanathan M. Espd: a pattern detection model underlying gene expression profiles. Bioinformatics 20 6 (2004) 829-838
15. Tavazoie S., Hughes J.D., Campbell M.J., Cho R.J., and Church G.M. Systematic determination of genetic network architecture. Nature Genet. 22 (1999) 281-285
16. Xing E.P., and Karp R.M. CLIFF: clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts. Bioinformatics Discovery Note 1 (2001) 1-9
17. Hartigan J.A., and Wong M.A. A k-means clustering algorithm. Appl. Statist. 28 (1979) 100-108
18. Bezdek J.C. Pattern Recognition with Fuzzy Objective Function Algorithms (1981), Kluwer Academic Publishers, Dordrecht
19. Ding C.H.Q. Analysis of gene expression profiles: class discovery and leaf ordering. Sixth Annual International Conference on Computational Biology (2002), ACM Press, New York 127-136
20. Vrahatis M.N., Boutsinas B., Alevizos P., and Pavlides G. The new k-windows algorithm for improving the k-means clustering algorithm. J. Complexity 18 (2002) 375-391
21. Jain A.K., Murty M.N., and Flynn P.J. Data clustering: a review. ACM Comput. Surv. 31 3 (1999) 264-323
22. Alizadeh A.A., et al. Distinct types of diffuse large b-cell lymphoma identified by gene expression profiling. Nature 403 6769 (2000) 503-511
23. Perou C.M., Jeffrey S.S., Van de Rijn M., Rees C.A., Eisen M.B., Ross D.T., Pergamenschikov A., Williams C.F., Zhu S.X., Lashkari D., Lee J.C., Shalon D., Brown P.O., and Botstein D. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc. Natl. Acad. Sci. USA 96 (1999) 9212-9217
24. Tamayo P., Slonim D., Mesirov Q., Zhu J., Kitareewan S., Dmitrovsky E., Lander E.S., and Golub T.R. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc. Natl. Acad. Sci. USA 96 (1999) 2907-2912
25. Alter O., Brown P.O., and Bostein D. Singular value decomposition for genome-wide expression data processing and modeling. Proc. Natl. Acad. Sci. USA 97 18 (2000) 10101-10106
26. Z. Szallasi, R. Somogyi, Genetic network analysis-the millennium opening version, in: Pacific Symposium of BioComputing Tutorial, 2001.
27. G.H. John, R. Kohavi, K. Pfleger, Irrelevant features and the subset selection problem, in: International Conference on Machine Learning, 1994, pp. 121-129.
28. Aggarwal C.C., Wolf J.L., Yu P.S., Procopiuc C., and Park J.S. Fast algorithms for projected clustering. 1999 ACM SIGMOD International Conference on Management of Data (1999), ACM Press, New York 61-72
29. Agrawal R., Gehrke J., Gunopulos D., and Raghavan P. Automatic subspace clustering of high dimensional data for data mining applications. 1998 ACM SIGMOD International Conference on Management of Data (1998), ACM Press, New York 94-105
30. Madeira S.C., and Oliveira A.L. Biclustering algorithms for biological data analysis: a survey. IEEE/ACM Trans. Comput. Biol. Bioinformatics 1 (2004) 24-45
31. Tasoulis D.K., and Vrahatis M.N. Unsupervised distributed clustering. Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Networks (2004), Innsbruck, Austria 347-351
32. Sander J., Ester M., Kriegel H.-P., and Xu X. Density-based clustering in spatial databases: the algorithm gdbscan and its applications. Data Mining Knowledge Discovery 2 2 (1998) 169-194
33. Boley D. Principal direction divisive partitioning. Data Mining and Knowledge Discovery 2 4 (1998) 325-344
34. Fritzke B. Growing cell structures a self-organizing network for unsupervised and supervised learning. Neural Networks 7 9 (1994) 1441-1460
35. Preparata F., and Shamos M. Computational Geometry (1985), Springer, New York, Berlin
36. Alevizos P. An algorithm for orthogonal range search in d ≥ 3 dimensions. Proceedings of the 14th European Workshop on Computational Geometry (1998), Barcelona
37. Bentley J.L., and Maurer H.A. Efficient worst-case data structures for range searching. Acta Inform. 13 (1980) 1551-1568
38. Chazelle B. Filtering search: a new approach to query-answering. SIAM J. Comput. 15 3 (1986) 703-724
39. V.P. Plagianakos, D.K. Tasoulis, M.N. Vrahatis, Hybrid dimension reduction approach for gene expression data classification, in: International Joint Conference on Neural Networks 2005 (IJCNN 2005), Post-Conference Workshop on Computational Intelligence Approaches for the Analysis of Bioinformatics Data, 2005.
40. D.K. Tasoulis, V.P. Plagianakos, M.N. Vrahatis, Unsupervised cluster analysis in bioinformatics, in: Fourth European Symposium on "Biomedical Engineering", 2004.
41. Tasoulis D.K., Plagianakos V.P., and Vrahatis M.N. Unsupervised clustering of bioinformatics data. European Symposium on Intelligent Technologies, Hybrid Systems and Their Implementation on Smart Adaptive Systems (2004), Eunite 47-53
42. G.D. Magoulas, V.P. Plagianakos, D.K. Tasoulis, M.N. Vrahatis, Tumor detection in colonoscopy using the unsupervised k-windows clustering algorithm and neural networks, in: Fourth European Symposium on "Biomedical Engineering", 2004.
43. Tasoulis D.K., Vladutu L., Plagianakos V.P., Bezerianos A., and Vrahatis M.N. On-line neural network training for automatic ischemia episode detection. In: Rutkowski L., Siekmann J.H., Tadeusiewicz R., and Zadeh L.A. (Eds). Lecture Notes in Computer Science vol. 2070 (2003), Springer, Berlin 1062-1068
44. Pavlidis N.G., Tasoulis D.K., and Vrahatis M.N. Financial forecasting through unsupervised clustering and evolutionary trained neural networks. Congress on Evolutionary Computation (2003), Canberra, Australia
45. Rigou M., Sirmakessis S., and Tsakalidis A. A computational geometry approach to web personalization. IEEE International Conference on E-Commerce Technology (CEC'04) (2004), San Diego, California 377-380
46. D.K. Tasoulis, M.N. Vrahatis, Novel approaches to unsupervised clustering through the k-windows algorithm, in: Knowledge Mining, Studies in Fuzziness and Soft Computing, 2005.
47. Ester M., Kriegel H.-P., Sander J., and Xu X. A density-based algorithm for discovering clusters in large spatial databases. Second International Conference on Data Mining KDD-96 (1996), Portland, Oregon 226-231
48. Zeimpekis D., and Gallopoulos E. PDDP(l): towards a flexing principal direction divisive partitioning clustering algorithms. In: Boley D., Dhillon I., Ghosh J., and Kogan J. (Eds). Proceedings of the IEEE ICDM '03 Workshop on Clustering Large Data Sets (2003), Melbourne, Florida 26-35
49. Kohonen T. Self-Organized Maps (1997), Springer, New York, Berlin
50. Thomas J.G., Olson J.M., Tapscott S.J., and Zhao L.P. An efficient and robust statistical modeling approach to discover differentially expressed genes using genomic expression profiles. Genome Res. 11 (2001) 1227-1236
51. Singh D., et al. Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 1 (2002) 203-209
52. Ye J., Li T., Xiong T., and Janardan R. Using uncorrelated discriminant analysis for tissue classification with gene expression data. IEEE ACM Trans. Comput. Biol. Bioinformatics 1 4 (2004) 181-190