Tag: BI Total 10 articles All cs.GNN other logic pytorch cs.Meta CL BI CV SE GNN IR OS 2023-03-27 International Journal of Molecular Sciences-2023 DeepTP：A Deep Learning Model for Thermophilic Protein Prediction 2023-03-27 Frontiers in Microbiology-2022 iThermo：A Sequence-Based Model for Identifying Thermophilic Proteins Using a Multi-Feature Fusion Strategy 2023-03-19 Bioinformatics-2023 Accurate and efficient protein sequence design through learning concise local environment of residues 2023-03-14 NIPS-2021 Language models enable zero-shot prediction of the effects of mutations on protein function 2023-03-14 ICML-2022 Tranception：protein fitness prediction with autoregressive transformers and inference-time retrieval 2023-02-02 ICML-2021 Learning inverse folding from millions of predicted structures 2023-01-24 ICLR-2021 Learning from Protein Structure with Geometric Vector Perceptrons 2023-01-18 bioRxiv-2022 Masked inverse folding with sequence transfer for protein representation learning 2023-01-17 bioRxiv-2021 Toward More General Embeddings for Protein Design：Harnessing Joint Representations of Sequence and Structure 2023-01-09 bioRxiv-2023 When Geometric Deep Learning Meets Pretrained Protein Language Models
2023-03-27 International Journal of Molecular Sciences-2023 DeepTP：A Deep Learning Model for Thermophilic Protein Prediction
2023-03-27 Frontiers in Microbiology-2022 iThermo：A Sequence-Based Model for Identifying Thermophilic Proteins Using a Multi-Feature Fusion Strategy
2023-03-19 Bioinformatics-2023 Accurate and efficient protein sequence design through learning concise local environment of residues
2023-03-14 NIPS-2021 Language models enable zero-shot prediction of the effects of mutations on protein function
2023-03-14 ICML-2022 Tranception：protein fitness prediction with autoregressive transformers and inference-time retrieval
2023-01-18 bioRxiv-2022 Masked inverse folding with sequence transfer for protein representation learning
2023-01-17 bioRxiv-2021 Toward More General Embeddings for Protein Design：Harnessing Joint Representations of Sequence and Structure
