Accurate prediction of cohesin and RNA Polymerase II-associated chromatin interactions using convolutional neural networks

The three-dimensional (3D) genome organization specifies how the distal regulatory elements in the linear genome interact with target genes to regulate transcription. Several experimental methods have been developed to study the 3D genome organization. However, these methods are, in general, expensive, technically challenging, and time-consuming. We present Convolutional Neural Networks-Chromatin Interaction Predictor (CNN-ChIPr), a machine learning method for predicting the relative strength of