• DocumentCode
    2010234
  • Title

    Bicluster Analysis of Genome-Wide Gene Expression

  • Author

    Chen, Kuanchung ; Hu, Yuh-Jyh

  • Author_Institution
    Dept. of Comput. Sci., Nat. Chiao Tung Univ., Hsinchu
  • fYear
    2006
  • fDate
    28-29 Sept. 2006
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    A number of biclustering approaches have been developed to mitigate the limitations of standard clustering algorithms. They have different problem formulation, search strategy and computational complexity. We proposed a new biclustering method based on the framework of market basket analysis in which a bicluster is described as a frequent itemset. As a feasibility test, we compared it with several standard clustering algorithms on a genome-wide yeast microarray dataset, and it showed very promising results. We later did a comparison between our approach and various current biclustering methods, following a systematic evaluation procedure recently published. The experimental results demonstrate that our new method outperforms the others
  • Keywords
    biology computing; genetics; pattern clustering; bicluster analysis; clustering algorithm; frequent itemset; genome-wide gene expression; market basket analysis; yeast microarray dataset; Algorithm design and analysis; Bioinformatics; Clustering algorithms; Computational complexity; Computer science; Educational institutions; Gene expression; Genomics; Itemsets; Standards development; biclustering; clustering; expression; microarray;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Bioinformatics and Computational Biology, 2006. CIBCB '06. 2006 IEEE Symposium on
  • Conference_Location
    Toronto, Ont.
  • Print_ISBN
    1-4244-0623-4
  • Electronic_ISBN
    1-4244-0624-2
  • Type

    conf

  • DOI
    10.1109/CIBCB.2006.330994
  • Filename
    4133176