c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression

Background: Computational methods for characterizing novel transcription factor binding sites search for sequence patterns or "motifs" that appear repeatedly in genomic regions of interest. Correlation-based motif finding strategies are used to identify motifs that correlate with expression data and do not rely on promoter sequences from a pre-determined set of genes. Results: In this work, we describe a method for predicting motifs that combines the correlationbased strategy with phylogenetic footprinting, where motifs are identified by evaluating orthologous sequence regions from multiple species. Our method, c-REDUCE, can account for variability at a motif position inferred from evolutionary information. c-REDUCE has been tested on ChIP-chip data for yeast transcription factors and on gene expression data in Drosophila. Conclusion: Our results indicate that utilizing sequence conservation information in addition to correlation-based methods improves the identification of ...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Katerina Kechris, Hao Li
• Keywords: BMCBI 2008, Gene Expression, Sequences, Transcription Factors