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Bioinformatics Advance Access originally published online on May 19, 2005
Bioinformatics 2005 21(14):3164-3165; doi:10.1093/bioinformatics/bti481
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

TAMO: a flexible, object-oriented framework for analyzing transcriptional regulation using DNA-sequence motifs

D. Benjamin Gordon 1, Lena Nekludova 1, Scott McCallum 1 and Ernest Fraenkel 1,2,*

1Whitehead Institute for Biomedical Research, Nine Cambridge Center Cambridge, MA 02142, USA
2MIT Computer Science and Artificial Intelligence Laboratory 32 Vassar Street, Cambridge, MA 02139, USA

*To whom correspondence should be addressed.

Summary: TAMO (Tools for Analysis of MOtifs) is an object-oriented computational framework for interpreting transcriptional regulation using DNA-sequence motifs. To simplify the application of multiple motif discovery programs to genome-wide data, TAMO provides a sophisticated motif object with interfaces to several popular programs. In addition, TAMO provides modules for integrating motif analysis with diverse data sources including genomic sequences, microarrays and various databases. Finally, TAMO includes tools for sequence analysis, algorithms for scoring, comparing and clustering motifs, and several useful statistical tests. Recently, we have applied these tools to analyze tens of thousands of motifs derived from hundreds of microarray experiments.

Availability: TAMO is a Python/C++ package and requires Python 2.3 or higher. Source code and documentation are available at http://web.wi.mit.edu/fraenkel/TAMO/

Contact: efraenkel{at}wi.mit.edu

Received on February 18, 2005; revised on April 14, 2005; accepted on April 30, 2005

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