Information theory empowers de novo discovery of structural motifs underpinning protein-DNA interactions

Determining where transcriptional regulators bind within the genome is paramount to understanding how gene regulation is controlled. Historically, position weight matrices (PWMs) have been used to define the binding preferences of DNA binding proteins. However, PWMs treat the identity of each base in a sequence as an independent and additive measure of binding preference, which can limit their utility. Models that consider higher order interactions between nearby bases yield greater success in predicting proteins' binding to DNA, but for many proteins there is still substantial room for improvement in predicting and understanding determinants of binding to DNA.