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Modern genomics experiments measure functional behaviors for many thousandsof DNA sequences. We suggest that, especially when these sequences are chosenat random, it is natural to compute correlation functions between sequences andmeasured behaviors. In simple models for the dependence of DNA flexibility onsequence, for example, correlation functions can be interpreted directly asinteraction parameters. Analysis of recent experiments shows that this issurprisingly effective, leading directly to extraction of distinct features forDNA flexibility and predictions that are as accurate as more complex models.This approach follows the conventional use of correlation functions instatistical physics and connects the search for relevant DNA sequence featuresto the search for relevant stimulus features in the analysis of sensoryneurons.

Searching for sequence features that control DNA flexibility