Open Access Journal

ISSN : 2394 - 6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

ISSN : 2394-6849 (Online)

Reference :

    1. Dongmin Seo, Yunsoo Choi, Min-Ho Lee, Seok-Jung Yu, ―Development of biological network crawling, clustering and visualization system‖, International Conference on Electrical Engineering/Electronics, Computer, Telecom and IT,pp.726-728,2017
    2. Amutha Priya and R. Lawrence, ―Algorithm for clustering analysis of gene expression data using MapReduce framework‖, International Conference on Data Storage and Data Engineering, pp.1-4, 2016
    3. Zhinwen Yu, Hanato Chen, Jiming,Wong, Han and Li, ―Adaptive Fuzzy consensus clustering framework for cluster analysis of cancer data‖, IEEE Transactions on Computational Biology and Bioinformatics,pp.1-14,2013
    4. Liming Wang and Xiaodong Wang, ―A Non-parametric Bayesian clustering for Gene expression data‖, IEEE Statistical Signal Processing Workshop, pp.556-559, 2012
    5. Damodar Edla,Seshaiah Machavarapu and Prasanta Jana, ―An Improved MST based clustering for Biological data‖,International Conference on Data Science and Engineering‖, pp.42-45,2012
    6. Ricardo Campello, Davoud Moulavi and Jorg Sander, ―A simpler and more accurate framework for clustering and visualization of biological data‖, IEEE Transactions on Computational Biology and Bioinformatics,Vol.9,No.6,pp.1850-1852,Nov/Dec.2012
    7. Xiao Zhang, Aichen Li, You Zhang and Yongpeng Xiao, ―Validity of Cluster technique for Genome expression data‖, Chinese Control and Decision Conference, pp.3737-3741, 2012
    8. Suvendu Kanungo, Gagadhar Sahoo and Manoj Gore, ―A Co-clustering technique for Gene expression data using Bi-partite Graph approach‖, IEEE Statistical Signal Processing Workshop, pp.1-5, 2010
    9. Guoqing Zhao and Wei Dang, ―An HMM based hierarchical clustering method for gene expression time series data‖, IEEE Statistical Signal Processing Workshop, pp.219-222, 2010
    10. Gunjan Gupta, Alexander Liu and Joydeep Ghosh, ―Automated hierarchical density shaving:A robust automated clustering and visualization framework for large biological data sets‖,IEEE Transactions on Computational Biology and Bioinformatics, Vol.7, No.2, April/May, 2010
    11. R. Xu, S. Damelin, B. Nadler, D. C. Wunsch II, "Clustering of highdimensional gene expression data with feature filtering methods and diffusion maps," Artificial Intelligence in Medicine, vol. 48, pp. 91-98, 2010.
    12. A. Mukhopadhyay, U. Maulik, 'Towards improving fuzzy clustering using support vector machine: Application to gene expression data," Pattern Recognition, vol. 42, pp. 2744-2763, 2009.
    13. Hae-Sang Park and,Chi-Hyuck Jun,‖A simple and fast algorithm for k-medoids clustering,‖ Expert System with applications,3336- 3341,2009.
    14. Amit Banerjee and Sushil J.Louis,‖ A Recursive Clustering Methodology using a genetic algorithm‖, IEEE Trans., 2007.
    15. L. Wang, F. Chu, W. Xie, "Accurate cancer classification using expressions of very few genes," IEEEIACM Transactions on Computational Biology and Bioinformatics, vol. 4 , issue I, pp. 40-53, 2007.
    16. C.M. Yang, B.K. Wan, X.F. Gao, "Internal validation technology research of the gene clustering result," Progress in Natural Science, vol. 17, no. 9, pp. 1181-1188,2007.
    17. H. J. Lin, F. W. Yang and Y. T. Kao‖, An efficient GAbased clustering technique, ―Tamkang Journal of Science and Engineering, vol. 8, no. 2,pp. 113-122, 2005.
    18. C. C. Lai,‖A novel clustering approach using hierarchical genetic algorithms,‖ Intelligent Automation and Soft Computing, vol. 11, no. 3,pp. 143-153, 2005.
    19. A. Schliep, I.G. Costa, C. Steinhoff, A. Schonhuth, "Analyzing gene expression time-courses," IEEEIACM Transactions on Computational Biology and Bioinformatics, vol. 2, no. 3, pp. 179-193,2005.
    20. X. Sun, Z.H. Lu, J.M. Xie, Foundation of bioinformatics, G.X. Chen, C.M. Zhao, Ed. Beijing, China: Tsinghua University Press, 2005.
    21. E. R. Hruschka, R. J. G. B. Campello, and L. N. de Castro,‖Improving the efficiency of a clustering genetic algorithm, In Advances in Artificial Intelligence,‖ IBERAMIA 2004, volume 3315 of LNCS, pages 861–870, 2004.
    22. Jiawei Han and M.kamber‖, Data mining: Concepts and Techniques,‖Morgan Kaufmann,2004.
    23. E.R. Hruschka, N.F.F. Ebecken,‖A genetic algorithm for cluster analysis‖,Intell. Data Anal. 7 (1) 15–25., 2003.
    24. Z. Shi, G. Joydeep, "A unified framework for modelbased clustering," Journal of Machine Learning Research, vol. 4, no 6, pp. 1001--I037, 2003
    25. N. Bolshakova, F. Azuaje, "Cluster validation techniques for genome expression data," Signal Processing, vol. 83, pp. 825-833,2003.
    26. S. Bandyopadhyay and U. Maulik,‖An evolutionary technique based on K-means algorithm for optimal clustering in RN,‖ Information Sciences,vol. 146, no.1-4, pp. 221-237,2002
    27. Y. Xu, V. Olman, D. Xu, "Clustering gene expression data using a graph-theoretic approach, an application of minimum spanning trees," Bioinformatics, vol. 18, no. 4, pp. 536-545,2002.
    28. L. Y. Tseng and S. B. Yang,‖A genetic approach to the automatic clustering algorithm,‖ Pattern Recognition, vol. 34, no. 2, pp. 415- 424,2001
    29. B.S. Everitt, S. Landau, M. Leese,‖Cluster Analysis,‖ Arnold Publishers, London, 2001.
    30. P. Baldi and S. Brunak, Bioinformatics: The machine learning approach, 2nd ed., T. Dietterich, Ed. London, England: The MIT Press, 2001.
    31. KY. Yeung, D.R. Haynor, W.L. Ruzzo, "Validating clustering for gene expression data," Bioinformatics, vol. 17, no. 4, pp. 309-318, 2001.
    32. V. R. Iyer, M. B. Eisen, D.T. Ross, G. Schuler, T. Moore, J.C. F. Lee, J.M. Trent, L. M. Staudt, HJ. James, M.S. Boguski, D. Lashkari, D. Shalon, D. Botstein, P.O. Brown, "The transcriptional program in the response of human fibroblasts to serum," Science, vol. 283, pp. 83-87, 1999.

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