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Nucleic Acids Research Advance Access originally published online on May 13, 2008
Nucleic Acids Research 2008 36(Web Server issue):W315-W319; doi:10.1093/nar/gkn265
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Nucleic Acids Research, 2008, Vol. 36, No. suppl_2 W315-W319
© 2008 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.


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AMIC@: All MIcroarray Clusterings @ once

Filippo Geraci, Marco Pellegrini* and M. Elena Renda

Istituto di Informatica e Telematica del C.N.R., Via Moruzzi 1, Pisa, Italy

*To whom correspondence should be addressed. Tel: +39 050 3152410; Fax: +39 050 3152593; Email: marco.pellegrini{at}iit.cnr.it

Received February 18, 2008. Revised April 17, 2008. Accepted April 21, 2008.

The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica.


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