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Bioinformatics Advance Access published online on May 19, 2005
Bioinformatics, 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@oupjournals.org
Received February 18, 2005
Revised April 14, 2005
Accepted April 30, 2005

Applications note

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 2

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


  Abstract

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 (Harbison et al., 2004).

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/.


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