Journal Article

Motif discovery and motif finding from genome-mapped DNase footprint data

Ivan V. Kulakovskiy, Alexander V. Favorov and Vsevolod J. Makeev

in Bioinformatics

Volume 25, issue 18, pages 2318-2325
Published in print September 2009 | ISSN: 1367-4803
Published online July 2009 | e-ISSN: 1460-2059 | DOI:
Motif discovery and motif finding from genome-mapped DNase footprint data

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Motivation: Footprint data is an important source of information on transcription factor recognition motifs. However, a footprinting fragment can contain no sequences similar to known protein recognition sites. Inspection of genome fragments nearby can help to identify missing site positions.

Results: Genome fragments containing footprints were supplied to a pipeline that constructed a position weight matrix (PWM) for different motif lengths and selected the optimal PWM. Fragments were aligned with the SeSiMCMC sampler and a new heuristic algorithm, Bigfoot. Footprints with missing hits were found for ∼50% of factors. Adding only 2 bp on both sides of a footprinting fragment recovered most hits. We automatically constructed motifs for 41 Drosophila factors. New motifs can recognize footprints with a greater sensitivity at the same false positive rate than existing models. Also we discuss possible overfitting of constructed motifs.

Availability: Software and the collection of regulatory motifs are freely available at


Supplementary information:

Journal Article.  6983 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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