@article {49128,
	title = {Accurate and sensitive quantification of protein-DNA binding affinity.},
	journal = {Proceedings of the National Academy of Sciences of the United States of America},
	volume = {115},
	year = {2018},
	month = {2018 Apr 02},
	pages = {E3692-701},
	abstract = {<p>Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes.</p>
},
	issn = {1091-6490},
	doi = {10.1073/pnas.1714376115},
	author = {Rastogi, Chaitanya and Rube, H Tomas and Kribelbauer, Judith F and Crocker, Justin and Loker, Ryan E and Martini, Gabriella D and Laptenko, Oleg and Freed-Pastor, William A and Prives, Carol and Stern, David L and Mann, Richard S and Bussemaker, Harmen J}
}
