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iMotifs: an integrated sequence motif visualization and analysis environment.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Piipari, Matias 
Down, Thomas A 
Saini, Harpreet 
Hubbard, Tim JP 

Abstract

MOTIVATION: Short sequence motifs are an important class of models in molecular biology, used most commonly for describing transcription factor binding site specificity patterns. High-throughput methods have been recently developed for detecting regulatory factor binding sites in vivo and in vitro and consequently high-quality binding site motif data are becoming available for increasing number of organisms and regulatory factors. Development of intuitive tools for the study of sequence motifs is therefore important. iMotifs is a graphical motif analysis environment that allows visualization of annotated sequence motifs and scored motif hits in sequences. It also offers motif inference with the sensitive NestedMICA algorithm, as well as overrepresentation and pairwise motif matching capabilities. All of the analysis functionality is provided without the need to convert between file formats or learn different command line interfaces. The application includes a bundled and graphically integrated version of the NestedMICA motif inference suite that has no outside dependencies. Problems associated with local deployment of software are therefore avoided. AVAILABILITY: iMotifs is licensed with the GNU Lesser General Public License v2.0 (LGPL 2.0). The software and its source is available at http://wiki.github.com/mz2/imotifs and can be run on Mac OS X Leopard (Intel/PowerPC). We also provide a cross-platform (Linux, OS X, Windows) LGPL 2.0 licensed library libxms for the Perl, Ruby, R and Objective-C programming languages for input and output of XMS formatted annotated sequence motif set files. CONTACT: matias.piipari@gmail.com; imotifs@googlegroups.com.

Description

Keywords

Algorithms, Base Sequence, Binding Sites, Computational Biology, Molecular Sequence Data, Sequence Alignment, Sequence Analysis, DNA, Software, User-Computer Interface

Journal Title

Bioinformatics

Conference Name

Journal ISSN

1367-4803
1367-4811

Volume Title

26

Publisher

Oxford University Press (OUP)