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Nucleic Acids Research 2006 34(Database Issue):D613-D616; doi:10.1093/nar/gkj022
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Nucleic Acids Research, 2006, Vol. 34, Database issue D613-D616
© The Author 2006. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oxfordjournals.org

Article

ITTACA: a new database for integrated tumor transcriptome array and clinical data analysis

Adil Elfilali1,2, Séverine Lair1,2, Catia Verbeke1,2, Philippe La Rosa1, François Radvanyi2 and Emmanuel Barillot1,*

1Institut Curie, Service Bioinformatique 26 rue d'Ulm, Paris, 75248 cedex 05, France 2Institut Curie, CNRS UMR 144 26 rue d'Ulm, Paris, 75248 cedex 05, France

*To whom correspondence should be addressed. Email: emmanuel.barillot{at}curie.fr

Received August 9, 2005. Revised September 19, 2005. Accepted September 19, 2005.

Transcriptome microarrays have become one of the tools of choice for investigating the genes involved in tumorigenesis and tumor progression, as well as finding new biomarkers and gene expression signatures for the diagnosis and prognosis of cancer. Here, we describe a new database for Integrated Tumor Transcriptome Array and Clinical data Analysis (ITTACA). ITTACA centralizes public datasets containing both gene expression and clinical data. ITTACA currently focuses on the types of cancer that are of particular interest to research teams at Institut Curie: breast carcinoma, bladder carcinoma and uveal melanoma. A web interface allows users to carry out different class comparison analyses, including the comparison of expression distribution profiles, tests for differential expression and patient survival analyses. ITTACA is complementary to other databases, such as GEO and SMD, because it offers a better integration of clinical data and different functionalities. It also offers more options for class comparison analyses when compared with similar projects such as Oncomine. For example, users can define their own patient groups according to clinical data or gene expression levels. This added flexibility and the user-friendly web interface makes ITTACA especially useful for comparing personal results with the results in the existing literature. ITTACA is accessible online at http://bioinfo.curie.fr/ittaca.


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