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Volumn , Issue , 2006, Pages 104-108

Consensus clustering for detection of overlapping clusters in microarray data

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; DATA MINING; GENES;

EID: 78449307810     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icdmw.2006.50     Document Type: Conference Paper
Times cited : (11)

References (14)
  • 2
    • 78449311373 scopus 로고    scopus 로고
    • Master's thesis, University of Texas at Austin
    • M. Deodhar. Consensus clustering of microarray data. Master's thesis, University of Texas at Austin, 2006. www.ece.utexas.edu/~deodhar/msthesis.pdf.
    • (2006) Consensus Clustering of Microarray Data
    • Deodhar, M.1
  • 3
    • 31844442747 scopus 로고    scopus 로고
    • A unified view of kernel k-means, spectral clustering and graph clustering
    • I. Dhillon, Y. Guan, and B. Kulis. A unified view of kernel k-means, spectral clustering and graph clustering. In UTCS Technical Report TR-04-05, 2005.
    • (2005) UTCS Technical Report TR-04-05
    • Dhillon, I.1    Guan, Y.2    Kulis, B.3
  • 7
    • 2542613410 scopus 로고    scopus 로고
    • Scalable clustering
    • N. Ye, editor, Lawrence Erlbaum Assoc.
    • J. Ghosh. Scalable clustering. In N. Ye, editor, The Handbook of Data Mining, pages 247-277. Lawrence Erlbaum Assoc., 2003.
    • (2003) The Handbook of Data Mining , pp. 247-277
    • Ghosh, J.1
  • 8
    • 0032681035 scopus 로고    scopus 로고
    • Multilevel k -way hypergraph partitioning
    • G. Karypis and V. Kumar. Multilevel k -way hypergraph partitioning. In Design Automation Conference, pages 343-348, 1999.
    • (1999) Design Automation Conference , pp. 343-348
    • Karypis, G.1    Kumar, V.2
  • 9
    • 0038724494 scopus 로고    scopus 로고
    • Consensus clustering-a resampling-based method for class discovery and visualization of gene expression microarray data
    • S. Monti, P. Tamayo, J. Mesirov, and T. Golub. Consensus clustering-a resampling-based method for class discovery and visualization of gene expression microarray data. In Journal of Machine Learning, pages 52: 91-118, 2003.
    • (2003) Journal of Machine Learning , vol.52 , pp. 91-118
    • Monti, S.1    Tamayo, P.2    Mesirov, J.3    Golub, T.4
  • 10
    • 0001820920 scopus 로고    scopus 로고
    • X-means: Extending K-means with efficient estimation of the number of clusters
    • Morgan Kaufmann, San Francisco, CA
    • D. Pelleg and A. Moore. X-means: Extending K-means with efficient estimation of the number of clusters. In Proc. 17th International Conf. on Machine Learning, pages 727-734. Morgan Kaufmann, San Francisco, CA, 2000.
    • (2000) Proc. 17th International Conf. on Machine Learning , pp. 727-734
    • Pelleg, D.1    Moore, A.2
  • 13
    • 24944539029 scopus 로고    scopus 로고
    • Consensus clustering and functional interpretation of gene-expression data
    • S. Swift, A. Tucker, V. Vinciotti, and N. Martin. Consensus clustering and functional interpretation of gene-expression data. In Genome Biology 5:R94, 2004.
    • (2004) Genome Biology , vol.5
    • Swift, S.1    Tucker, A.2    Vinciotti, V.3    Martin, N.4
  • 14
    • 0001562581 scopus 로고    scopus 로고
    • Linear and order statistics combiners for pattern classification
    • A. Sharkey, editor, Springer-Verlag
    • K. Tumer and J. Ghosh. Linear and order statistics combiners for pattern classification. In A. Sharkey, editor, Combining Artificial Neural Nets, pages 127-162. Springer-Verlag, 1999.
    • (1999) Combining Artificial Neural Nets , pp. 127-162
    • Tumer, K.1    Ghosh, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.