Direct physical information that describes where transcription factors, nucleosomes, modified histones, RNA polymerase II, and other key proteins interact with the genome provides an invaluable mechanistic foundation for understanding complex programs of gene regulation. We present a new method, Joint Binding Deconvolution (JBD), that uses additional easily obtainable experimental data about Chromatin Immunoprecipitation (ChIP) to improve the spatial resolution of the transcription factor

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... g locations inferred from ChIP-Chip data. Based on this probabilistic model of binding data, we further pursue improved spatial 1 resolution by using sequence information. We produce positional priors that link ChIP-Chip data to sequence data by guiding motif discovery to inferred protein-DNA binding sites. We present results on the yeast transcription factors Gcn4 and Mig2 to demonstrate JBD's superior spatial resolution and show that positional priors allow computational discovery of the Mig2 motif when a standard approach fails.