Abstract
The identification of binding sites for transcription factors regulating gene transcription is one of the most important and challenging problems in molecular biology and bioinformatics. Here we present an algorithm that, given a set of promoters from co–regulated genes, identifies over-represented binding sites by using profiles (position specific frequency matrices) defining the sequence binding specificity of known TFs as well as matching statistics on a whole–genome level, bypassing the need of defining matching thresholds and/or the use of homologous sequences. Preliminary tests performed on experimentally validated sequence sets are very promising; moreover, the same algorithm is suitable also for the use with any model of the binding specificity of TFs.
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Pavesi, G., Zambelli, F. (2007). Prediction of over Represented Transcription Factor Binding Sites in Co-regulated Genes Using Whole Genome Matching Statistics. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_83
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DOI: https://doi.org/10.1007/978-3-540-73400-0_83
Publisher Name: Springer, Berlin, Heidelberg
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