RANovo employs a CNN with a deep residual network architecture . Thus, in addition to passing information directly from layer to layer, RANovo contains residual connections that pass information from shallow layers to much deeper layers in the network. The model also incorporates the squeeze-andexcitation mechanism , which aims to automatically identify important pairwise relationships between input features. The model consists of two convolutional layers and two fully-connected layers.