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Open Access Highly Accessed Methodology article

LASAGNA: A novel algorithm for transcription factor binding site alignment

Chih Lee and Chun-Hsi Huang*

Author Affiliations

Department of Computer Science and Engineering, University of Connecticut, Fairfield Road, Storrs, CT 06269, USA

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BMC Bioinformatics 2013, 14:108  doi:10.1186/1471-2105-14-108

Published: 24 March 2013

Additional files

Additional file 1:

LASAGNA-ChIP flowchart.

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Additional file 2:

Distribution of Ks by species and conserved domain.

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Additional file 3:

Summary of 38 mouse ChIP-seq experiments. Each row shows the track name in the UCSC Genome Browser, cell type, target TF, number of peak sequences as well as the minimum, maximum, mean and standard deviation of peak sequence length.

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Additional file 4:

Motifs found by LASAGNA-ChIP and MEME. For each ChIP-seq experiment, the sequence logos of motifs found by LASAGNA-ChIP and MEME are shown. The matching motifs in the TRANSFAC Public and UniPROBE databases found by TOMTOM are listed below each sequence logo. The first ChIPed motif TF is highlighted in yellow if it is among the matching motifs. When the found motif does not resemble those of the ChIPed TF, the first cofactor of the ChIPed TF is highlighted in blue if it is among the matching motifs. Other possibly correct matches are highlighted in green.

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Additional file 5:

List of LASAGNA-built models based on TRANSFAC/ORegAnno TFBSs. Only models whose counterparts can be found in matrices in TRANSFAC Public are listed. The IC and number of sites are shown for each model.

Format: XLS Size: 49KB Download file

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Open Data