Shift augmentation improves DNA convolutional neural network indel effect predictions
Anna Korsakova, Divyanshi Srivastava, David R. Kelley
This paper improves DNA CNNs' ability to predict indel effects on gene regulation by addressing technical variance through shift augmentation and introduces an interpretation technique validated with experimental data.