Probabilistic Arithmetic Automata and Their Application to Pattern Matching Statistics
CPM '08 Proceedings of the 19th annual symposium on Combinatorial Pattern Matching
Modeling the competitive effects of nucleosomes on transcription factors binding
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
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Motivation: Theoretical efforts to understand the regulation of gene expression are traditionally centered around the identification of transcription factor binding sites at specific DNA positions. More recently these efforts have been supplemented by experimental data for relative binding affinities of proteins to longer intergenic sequences. The question arises to what extent these two approaches converge. In this paper, we adopt a physical binding model to predict the relative binding affinity of a transcription factor for a given sequence. Results: We find that a significant fraction of genome-wide binding data in yeast can be accounted for by simple count matrices and a physical model with only two parameters. We demonstrate that our approach is both conceptually and practically more powerful than traditional methods, which require selection of a cutoff. Our analysis yields biologically meaningful parameters, suitable for predicting relative binding affinities in the absence of experimental binding data. Availability: The C source code for our TRAP program is freely available for non-commercial use at http://www.molgen.mpg.de/~manke/papers/TFaffinities/ Contact: vingron@molgen.mpg.de