A mixture model-based approach to the clustering of microarray expression data

@article{McLachlan2002AMM,
  title={A mixture model-based approach to the clustering of microarray expression data},
  author={G. McLachlan and Richard Bean and D. Peel},
  journal={Bioinformatics},
  year={2002},
  volume={18 3},
  pages={
          413-22
        }
}
  • G. McLachlan, Richard Bean, D. Peel
  • Published 2002
  • Computer Science, Medicine, Mathematics
  • Bioinformatics
  • MOTIVATION This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the… CONTINUE READING
    573 Citations
    On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples
    • 12
    • Highly Influenced
    • PDF
    Classification of microarray data with factor mixture models
    • 27
    • Highly Influenced
    • PDF
    Clustering of gene expression data via normal mixture models.
    • 4
    Application of Gene Shaving and Mixture Models to Cluster Microarray Gene Expression Data
    • 5
    • Highly Influenced
    • PDF
    Model-based clustering of microarray expression data via latent Gaussian mixture models
    • 162
    • PDF
    Clustering gene expression profiles using Gaussian mixture model
    • PDF

    References

    SHOWING 1-10 OF 19 REFERENCES
    Coupled two-way clustering analysis of gene microarray data.
    • G. Getz, E. Levine, E. Domany
    • Biology, Physics
    • Proceedings of the National Academy of Sciences of the United States of America
    • 2000
    • 869
    • PDF
    CLIFF: clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts
    • 238
    • PDF
    Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays.
    • U. Alon, N. Barkai, +4 authors A. Levine
    • Biology, Medicine
    • Proceedings of the National Academy of Sciences of the United States of America
    • 1999
    • 4,060
    • Highly Influential
    • PDF
    Tumor classification by partial least squares using microarray gene expression data
    • 807
    • PDF
    Cluster analysis and display of genome-wide expression patterns
    • 6,078
    • PDF
    Clustering Gene Expression Patterns
    • 816
    • PDF
    'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns
    • 617
    • PDF
    Identifying marker genes in transcription profiling data using a mixture of feature relevance experts.
    • 114
    • Highly Influential
    • PDF
    Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
    • 2,650
    • PDF
    Tissue classification with gene expression profiles
    • 253
    • Highly Influential
    • PDF