Abstract
Transcription Factors (TFs) control transcription by binding to specific sites in the promoter regions of the target genes, which can be modelled by structured motifs. In this paper we propose AliBiMotif, a method combining sequence alignment and a biclustering approach based on efficient string matching techniques using suffix trees to unravel approximately conserved sets of blocks (structured motifs) while straightforwardly disregarding non-conserved stretches in-between. The ability to ignore the width of non-conserved regions is a major advantage of the proposed method over other motif finders, as the lengths of the binding sites are usually easier to estimate than the separating distances.
Original language | English |
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Pages (from-to) | 196-215 |
Number of pages | 20 |
Journal | International Journal of Data Mining and Bioinformatics |
Volume | 6 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Keywords
- biclustering
- sequence alignment
- motif finding algorithm
- structured motif identification
- binding site
- TF
- transcription factor
- TFBS
- cis-regulatory module discovery
- promoter region
- motif finder
- integrative mining