Statistical Machine Learning Methods Reveal Structural Mechanisms of Protein-DNA Binding

With the availability of a large amount of experimentally solved three-dimensional structures of transcription factor-DNA complexes and DNA sequence data from high-throughput binding assays, we developed statistical machine learning and deep learning methods that identify features of nucleic acids and proteins that are essential for protein-DNA readout and binding specificity. This talk will introduce such approaches and the new possibilities that such computational approaches provide for answering biological questions that relate to molecular recognition and gene regulation.