Skip Navigation



Bioinformatics Advance Access published online on May 7, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm238
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
23/14/1843    most recent
btm238v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
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 Xiang, Z.
Right arrow Articles by He, Y.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Xiang, Z.
Right arrow Articles by He, Y.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

CRCView: A web server for analyzing and visualizing microarray gene expression data using model-based clustering

Zuoshuang Xiang 1, Zhaohui Qin 2,3 and Yongqun He 1,3,4,*

1Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI.
2Department of Biostatistics, University of Michigan, Ann Arbor, MI.
3Bioinformatics Program, University of Michigan, Ann Arbor, MI.
4Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI.

*To whom correspondence should be addressed. Dr. Yongqun He, E-mail: yongqunh{at}umich.edu


  Abstract

Summary: CRCView is a user-friendly point-and-click web server for analyzing and visualizing microarray gene expression data using a Dirichlet process mixture model-based clustering algorithm. CRCView is designed to clustering genes based on their expression profiles. It allows flexible input data format, rich graphical illustration, as well as integrated GO term based annotation/interpretation of clustering results.

Availability: http://helab.bioinformatics.med.umich.edu/crcview/

Associate Editor: Dr. Olga Troyanskaya

Received on March 15, 2007; revised on April 22, 2007; accepted on April 26, 2007

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
F. Achcar, J.-M. Camadro, and D. Mestivier
AutoClass@IJM: a powerful tool for Bayesian classification of heterogeneous data in biology
Nucleic Acids Res., July 1, 2009; 37(suppl_2): W63 - W67.
[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.