Volume 10 Supplement 13
KIRMES: kernel-based identification of regulatory modules in euchromatic sequences
© Schultheiss et al; licensee BioMed Central Ltd. 2009
Published: 19 October 2009
We predict transcription factor (TF) target genes based on their regulatory sequence. A TF binding site is a short segment (~10 bp) near a gene's regulatory region that is recognized by respective TFs. Overrepresented motifs can be identified in regulatory sequences of a set of genes that is enriched with targets for a specific TF. Gibbs-sampling methods that try to identify position weight matrices to characterize binding sites have been successful for small genomes, but are problematic in higher eukaryotes, where motifs are degenerate and form cis-regulatory modules .
We compared our method to a state-of-the-art Gibbs sampler, PRIORITY , on its own dataset with the published settings with respect to successful classification. We achieve correct predictions on 74% of their sets vs. 63% for PRIORITY. We let KIRMES classify gene sets obtained from microarrays of Arabidopsis thaliana. Using conservation as weighting for the WDS kernel improves performance. These results illustrate the power of our approach in exploiting the relationship between motifs as well as conservation to improve the recognition of TF targets. Interpretable results and an easy-to-use web service make this a valuable tool for any researcher interested in gene regulation.
- Gupta M, Liu J: De novo cis-regulatory module elicitation for eukaryotic genomes. Proc Natl Acad Sci USA 2005, 102(20):7079–7084.PubMed CentralView ArticlePubMedGoogle Scholar
- Schultheiss SJ, Busch W, Lohmann JU, Kohlbacher O, Rätsch G: KIRMES: Kernel-based identification of regulatory modules in euchromatic sequences. Bioinformatics 2009. epub: 23 April 2009. epub: 23 April 2009.Google Scholar
- Sonnenburg S, Zien A, Philips P, Rätsch G: POIMs: Positional Oligomer Importance Matrices – understanding support vector machine-based signal detectors. Bioinformatics 2008, 24(13):i6–14.PubMed CentralView ArticlePubMedGoogle Scholar
- Gordan R, Narlikar L, Hartemink A: A fast, alignment-free, conservation-based method for transcription factor binding site discovery. In Lecture Notes in Computer Science: RECOMB 2008. Volume 4955. Springer, Heidelberg, Germany; 98–111.
This article is published under license to BioMed Central Ltd.