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Nucleic Acids Research 2005 33(Web Server Issue):W654-W658; doi:10.1093/nar/gki350
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© The Author 2005. 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}oupjournals.org


Article

T-STAG: resource and web-interface for tissue-specific transcripts and genes

Shobhit Gupta*, Martin Vingron and Stefan A. Haas

Computational Molecular Biology, Max Planck Institute for Molecular Genetics Ihnestraße 63-73, D-14195 Berlin, Germany

*To whom correspondence should be addressed. Tel: +49 30 8413 1163; Fax: +49 30 8413 1152; Email: gupta{at}molgen.mpg.de

Received October 21, 2004. Revised November 24, 2004. Accepted November 24, 2004.

T-STAG (tissue-specific transcripts and genes) is a resource and web-interface, designated to analyze tissue/tumor-specific expression patterns in human and mouse transcriptomes. It integrates our refined prediction of specific expression patterns both in genes as well as in individual isoforms with man–mouse orthology data. In combination with the features for combining/contrasting the genes expressed in different tissues, T-STAG implicates important biological applications, such as the detection of differentially expressed genes in tumors, the retrieval of orthologs with significant expression in the same tissue etc. Additionally, our refined categorization of expressed sequence tags (ESTs) according to the normalization of cDNA libraries allows searching for putative low-abundant transcripts. The results are tightly linked to our visualization tools, GeneNest (expression patterns of genes) and SpliceNest (gene structure and alternative splicing). The user-friendly interface of T-STAG offers a platform for comprehensive analysis of tissue and/or tumor-specific expression patterns revealed by the EST data. T-STAG is freely accessible at http://tstag.molgen.mpg.de.


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