next up previous
Up: The mosclust R package: Previous: Software download and documentation


D. Achlioptas.
Database-friendly random projections.
In P. Buneman, editor, Proc. ACM Symp. on the Principles of Database Systems, Contemporary Mathematics, pages 274-281, New York, NY, USA, 2001. ACM Press.

A. Alizadeh, M.B. Eisen, R.E. Davis, C. Ma, I.S. Lossos, A. Rosenwald, J.C. Boldrick, H. Sabet, T. Tran, X. Yu, J.I. Powell, L. Yang, G.E. Marti, T. Moore, J. Hudson, L. Lu, D.B. Lewis, R. Tibshirani, G. Sherlock, W.C. Chan, T.C. Greiner, D.D. Weisenburger, J.O. Armitage, R. Warnke, R. Levy, W. Wilson, M.R. Grever, J.C. Byrd, D. Botstein, P.O. Brown, and L.M. Staudt.
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.
Nature, 403:503-511, 2000.

A. Alizadeh et al.
The lymphochip: a specialized cDNA microarray for genomic-scale analysis of gene expression in normal and malignant lymphocytes.
In Cold Spring Harbor Symp. Quant. Biol., 2001.

A. Ben-Hur, A. Ellisseeff, and I. Guyon.
A stability based method for discovering structure in clustered data.
In R.B. Altman, A.K. Dunker, L. Hunter, T. Klein, and K. Lauderdale, editors, Pacific Symposium on Biocomputing, volume 7, pages 6-17, Lihue, Hawaii, USA, 2002. World Scientific.

A. Bertoni and G. Valentini.
Discovering significant structures in clustered data through bernstein inequality.
In CISI '06, Conferenza Italiana Sistemi Intelligenti, Ancona, Italy, 2006.
available at valenti/papers/bertoni-vale-cisi06.pdf.

A. Bertoni and G. Valentini.
Model order selection for clustered bio-molecular data.
In J. Rousu, S. Kaski, and E. Ukkonen, editors, Probabilistic Modeling and Machine Learning in Structural and Systems Biology, pages 85-90, Tuusula, Finland, 2006. Helsinki University Printing House.

A. Bertoni and G. Valentini.
Randomized maps for assessing the reliability of patients clusters in DNA microarray data analyses.
Artificial Intelligence in Medicine, 37(2):85-109, 2006.

M. Bittner, P. Meltzer, Y. Chen, Y. Jiang, E. Seftor, M. Hendrix, M. Radmacher, R. Simon, Z. Yakhini, A. Ben-Dor, N. Sampas, E. Dougherty, E. Wang, F. Marincola, C. Gooden, J. Lueders, A. Glatfelter, P. Pollock, J. Carpten, E. Gillanders, D. Leja, K. Dietrich, C. Beaudry, M. Berens, D. Alberts, and V. Sondak.
Molecular classification of malignant melanoma by gene expression profiling.
Nature, 406:536-540, 2000.

S. Dudoit and J. Fridlyand.
A prediction-based resampling method for estimating the number of clusters in a dataset.
Genome Biology, 3(7):1-21, 2002.

T.R. Golub et al.
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring.
Science, 286:531-537, 1999.

J. Handl, J. Knowles, and D. Kell.
Computational cluster validation in post-genomic data analysis.
Bioinformatics, 21(15):3201-3215, 2005.

W. Hoeffding.
Probability inequalities for sums of independent random variables.
J. Amer. Statist. Assoc., 58:13-30, 1963.

A.K. Jain and R.C. Dubes.
Algorithms for clustering data.
Prentice Hall, Englewood Cliffs, NJ, 1988.

A.K. Jain, M.N. Murty, and P.J. Flynn.
Data Clustering: a Review.
ACM Computing Surveys, 31(3):264-323, 1999.

M.K. Kerr and G.A. Curchill.
Bootstrapping cluster analysis: assessing the reliability of conclusions from microarray experiments.
PNAS, 98:8961-8965, 2001.

T. Lange, V. Roth, M. Braun, and J. Buhmann.
Stability-based validation of clustering solutions.
Neural Computation, 16:1299-1323, 2004.

L.M. McShane, D. Radmacher, B. Freidlin, R. Yu, M.C. Li, and R. Simon.
Method for assessing reproducibility of clustering patterns observed in analyses of microarray data.
Bioinformatics, 18(11):1462-1469, 2002.

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.
Machine Learning, 52:91-118, 2003.

W. Rand.
Objective criteria for the evaluation of clustering methods.
J. Am. Stat. Assoc., 66:846-850, 1971.

M. Smolkin and D. Gosh.
Cluster stability scores for microarray data in cancer studies.
BMC Bioinformatics, 36(4), 2003.

G. Valentini.
Clusterv: a tool for assessing the reliability of clusters discovered in DNA microarray data.
Bioinformatics, 22(3):369-370, 2006.