Combination of gene clusterings enhances biological validity

[1]  Ron Shamir,et al.  Scoring clustering solutions by their biological relevance , 2003, Bioinform..

[2]  Søren Brunak,et al.  Protein feature based identification of cell cycle regulated proteins in yeast. , 2003, Journal of Molecular Biology.

[3]  Francisco Azuaje,et al.  Cluster validation techniques for genome expression data , 2003, Signal Process..

[4]  Susmita Datta,et al.  Comparisons and validation of statistical clustering techniques for microarray gene expression data , 2003, Bioinform..

[5]  Kathleen Marchal,et al.  Functional bioinformatics of microarray data: from expression to regulation , 2002, Proc. IEEE.

[6]  Francis D. Gibbons,et al.  Judging the quality of gene expression-based clustering methods using gene annotation. , 2002, Genome research.

[7]  Francisco Azuaje,et al.  A cluster validity framework for genome expression data , 2002, Bioinform..

[8]  R. Tibshirani,et al.  Missing value estimation methods for DNA microarrays , 2001, Bioinform..

[9]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

[10]  Ronald W. Davis,et al.  A genome-wide transcriptional analysis of the mitotic cell cycle. , 1998, Molecular cell.

[11]  Douglas H. Fisher,et al.  Iterative Optimization and Simplification of Hierarchical Clusterings , 1996, J. Artif. Intell. Res..

[12]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[13]  R. Lyman Ott.,et al.  An introduction to statistical methods and data analysis , 1977 .