Forest Yang

1 month ago | biorxiv.org | Katherine S. Pollard |Nilah M. Ioannidis |Ryan L. Keivanfar |Forest Yang

AbstractDeep learning models in genomics that predict molecular phenotypes from DNA sequence traditionally focus on one-hot encoded representations. Here, we develop a novel model that extends this approach by incorporating DNA structural attributes indicative of local shape alongside canonical sequence inputs. This augmentation provides an additional axis for model interpretability and aids in identifying regulatory patterns not apparent from sequence alone.