A paper list of deep learning implementations in protein field
A list of deep learning implementations in protein field 简体中文
Generative models for graph-based protein design
[NIPS 2019]
[Github]
Learning protein sequence embeddings using information from structure
[ICLR 2019]
[Github]
Evaluating protein transfer learning with TAPE
[NIPS 2019]
[Github]
SignalP 5.0 improves signal peptide predictions using deep neural networks
Almagro Armenteros, J.J., Tsirigos, K.D., Sønderby, C.K. et al. 2019
[Nature Methods]
[Web server]
Unified rational protein engineering with sequence-based deep representation learning
Alley, E.C., Khimulya, G., Biswas, S. et al. 2019
[Nature Methods]
[Github]
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Das P, Sercu T, Wadhawan K, et al. 2020
[NIPS 2020]
[Web server]
End-to-End Learning on 3D Protein Structure for Interface Prediction
Townshend R, Bedi R, Suriana P, et al. 2019
[NIPS 2019]
[Github]
Energy-based models for atomic-resolution protein conformations
Du Y, Meier J, Ma J, et al. 2020
[ICLR 2020]
[Github]
Learning Protein Structure with a Differentiable Simulator
Ingraham J, Riesselman A J, Sander C, et al. 2019
[ICLR 2019]
[Github]
Human-level Protein Localization with Convolutional Neural Networks
Rumetshofer E, Hofmarcher M, Röhrl C, et al. 2019
[ICLR 2019]
[Github]
Learning Data-Driven Drug-Target-Disease Interaction via Neural Tensor Network
Chen H, Li J 2020
[IJCAI 2020]
Deep Learning of High-Order Interactions for Protein Interface Prediction
Liu Y, Yuan H, Cai L, et al. 2020
[KDD 2020]
DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction
Lin X, Zhao K, Xiao T, et al. 2020
[ECAI 2020]
[Github]
Improved protein structure prediction using potentials from deep learning
Senior A W, Evans R, Jumper J, et al. 2020
[Nature]
[Github]
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