… Computational protein folding and design have recently received attention from the …
Several recent single-model QA works are based on deep learning: 3DCNN and Ornate adopt a …

… novel deep convolutional networks to predict the local and global quality of a protein model
… are promising techniques for protein model quality assessment. In the near future, we will …

… Many methods for protein folding QA have already been developed. The goal of these …
Specifically, convolutional neural networks (CNN, also sometimes referred to as deep learning) …

… based on 3D voxel atomic representation and 3D convolutional network. The input density
map … structure prediction, the dynamic combination of model quality assessment and folding …

… To tackle the problem of model quality estimation from deep learning perspective, one …
GCN to the protein model quality assessment problem. We show that, with 20-fold less learnable …

… These deep learning methods often use low-level features such as RGB values of each …
-deep learning methods with high-level features. In such studies, convolutional neural networks (…

… Fold recognition assumes that natural proteins fold in similar … deep learning method for
protein model quality assessment. … International Joint Conference on Neural Networks (IJCNN), …

… that by using a powerful deep learning technique, even with only a personal computer we
can predict new folds much more … This method also works well on membrane protein folding. …

… some insights into the key fold-determining residues in proteins. … until 2019 for quality
assessment of protein structures. Here, we … The Deep Learning network used in RaptorX to predict …

… GNNRefine uses a graph convolution network with invariant features for protein model …
Under our testing environment, the deep learning model can handle proteins with length up to …