Searching for sequence features that control DNA flexibility

Modern genomics experiments measure functional behaviors for many thousands of DNA sequences. Using correlation functions between sequences and measured behaviors, we developed a simple physical model interpreting such experimental outputs. Analysis recent high throughput data on mechanics shows that this is highly effective, leading directly to the extraction distinct features flexibility predictions comparable more complex machine learning models. Our approach follows conventional use in statistical physics connects search relevant sequence stimulus sensory neurons.