Skip Navigation

Bioinformatics 2005 21(Suppl 1):i144-i151; doi:10.1093/bioinformatics/bti1041
This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Dueck, D.
Right arrow Articles by Frey, B. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Dueck, D.
Right arrow Articles by Frey, B. J.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Multi-way clustering of microarray data using probabilistic sparse matrix factorization

Delbert Dueck *, Quaid D. Morris and Brendan J. Frey

Department of Electrical and Computer Engineering, University of Toronto Toronto, Ontario, Canada M5S 3G4

*To whom correspondence should be addressed.

Motivation: We address the problem of multi-way clustering of microarray data using a generative model. Our algorithm, probabilistic sparse matrix factorization (PSMF), is a probabilistic extension of a previous hard-decision algorithm for this problem. PSMF allows for varying levels of sensor noise in the data, uncertainty in the hidden prototypes used to explain the data and uncertainty as to the prototypes selected to explain each data vector.

Results: We present experimental results demonstrating that our method can better recover functionally-relevant clusterings in mRNA expression data than standard clustering techniques, including hierarchical agglomerative clustering, and we show that by computing probabilities instead of point estimates, our method avoids converging to poor solutions.

Contact: delbert{at}psi.toronto.edu

Received on January 15, 2005; accepted on March 27, 2005

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Nucleic Acids ResHome page
E. Mejia-Roa, P. Carmona-Saez, R. Nogales, C. Vicente, M. Vazquez, X. Y. Yang, C. Garcia, F. Tirado, and A. Pascual-Montano
bioNMF: a web-based tool for nonnegative matrix factorization in biology
Nucleic Acids Res., July 1, 2008; 36(suppl_2): W523 - W528.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H. Kim and H. Park
Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis
Bioinformatics, June 15, 2007; 23(12): 1495 - 1502.
[Abstract] [Full Text] [PDF]

Home page
 Proc. Natl. Acad. Sci. USAHome page
P. Tamayo, D. Scanfeld, B. L. Ebert, M. A. Gillette, C. W. M. Roberts, and J. P. Mesirov
Metagene projection for cross-platform, cross-species characterization of global transcriptional states
PNAS, April 3, 2007; 104(14): 5959 - 5964.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H. Li, Y. Sun, and M. Zhan
The discovery of transcriptional modules by a two-stage matrix decomposition approach
Bioinformatics, February 15, 2007; 23(4): 473 - 479.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
A. W. Schreiber and U. Baumann
A framework for gene expression analysis
Bioinformatics, January 15, 2007; 23(2): 191 - 197.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.