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Nucleic Acids Research Advance Access originally published online on May 27, 2009
Nucleic Acids Research 2009 37(Web Server issue):W63-W67; doi:10.1093/nar/gkp430
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Nucleic Acids Research, 2009, Vol. 37, No. suppl_2 W63-W67
© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Articles

AutoClass@IJM: a powerful tool for Bayesian classification of heterogeneous data in biology

Fiona Achcar1,2, Jean-Michel Camadro2 and Denis Mestivier1,*

1‘Modeling in Integrative Biology’ Group and 2‘Protein Engineering and Metabolic Control’ Group, Jacques Monod Institute, UMR7592 CNRS and Univ Paris-Diderot, Bâtiment Buffon, 15 rue Hélène Brion, 75205 Paris Cedex 13, France

*To whom correspondence should be addressed. Tel: +33 (0)157278055; Fax: +33 (0)157278101; Email: mestivier{at}ijm.jussieu.fr

Received January 31, 2009. Revised April 23, 2009. Accepted May 11, 2009.

Recently, several theoretical and applied studies have shown that unsupervised Bayesian classification systems are of particular relevance for biological studies. However, these systems have not yet fully reached the biological community mainly because there are few freely available dedicated computer programs, and Bayesian clustering algorithms are known to be time consuming, which limits their usefulness when using personal computers. To overcome these limitations, we developed AutoClass{at}IJM, a computational resource with a web interface to AutoClass, a powerful unsupervised Bayesian classification system developed by the Ames Research Center at N.A.S.A. AutoClass has many powerful features with broad applications in biological sciences: (i) it determines the number of classes automatically, (ii) it allows the user to mix discrete and real valued data, (iii) it handles missing values. End users upload their data sets through our web interface; computations are then queued in our cluster server. When the clustering is completed, an URL to the results is sent back to the user by e-mail. AutoClass{at}IJM is freely available at: http://ytat2.ijm.univ-paris-diderot.fr/AutoclassAtIJM.html.


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