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Nucleic Acids Research 2006 34(Web Server issue):W369-W373; doi:10.1093/nar/gkl198
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© 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@oxfordjournals.org


Article

MEME: discovering and analyzing DNA and protein sequence motifs

Timothy L. Bailey*, Nadya Williams1, Chris Misleh1 and Wilfred W. Li1

Institute of Molecular Bioscience, The University of Queensland St Lucia, QLD 4072, Australia 1 SDSC, UCSD, La Jolla CA, USA

*To whom correspondence should be addressed. Tel: +61 7 3346 2614; Fax: +61 7 3346 2101; Email: t.bailey{at}imb.uq.edu.au

Received February 14, 2006. Revised March 21, 2006. Accepted March 21, 2006.

MEME (Multiple EM for Motif Elicitation) is one of the most widely used tools for searching for novel ‘signals’ in sets of biological sequences. Applications include the discovery of new transcription factor binding sites and protein domains. MEME works by searching for repeated, ungapped sequence patterns that occur in the DNA or protein sequences provided by the user. Users can perform MEME searches via the web server hosted by the National Biomedical Computation Resource (http://meme.nbcr.net) and several mirror sites. Through the same web server, users can also access the Motif Alignment and Search Tool to search sequence databases for matches to motifs encoded in several popular formats. By clicking on buttons in the MEME output, users can compare the motifs discovered in their input sequences with databases of known motifs, search sequence databases for matches to the motifs and display the motifs in various formats. This article describes the freely accessible web server and its architecture, and discusses ways to use MEME effectively to find new sequence patterns in biological sequences and analyze their significance.


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