Shuangjia Zheng

Orcid: 0000-0001-9747-4285

According to our database1, Shuangjia Zheng authored at least 45 papers between 2019 and 2024.

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Bibliography

2024
Deep generative design of RNA aptamers using structural predictions.
Nat. Comput. Sci., November, 2024

Self-Supervised Contrastive Molecular Representation Learning with a Chemical Synthesis Knowledge Graph.
J. Chem. Inf. Model., 2024

Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization.
CoRR, 2024

EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics.
CoRR, 2024

Reactzyme: A Benchmark for Enzyme-Reaction Prediction.
CoRR, 2024

Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks.
CoRR, 2024

Effective Protein-Protein Interaction Exploration with PPIretrieval.
CoRR, 2024

Causal Subgraph Learning for Generalizable Inductive Relation Prediction.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023
Subgraph-Aware Few-Shot Inductive Link Prediction Via Meta-Learning.
IEEE Trans. Knowl. Data Eng., June, 2023

Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis.
IEEE Trans. Affect. Comput., 2023

Mixup-Augmented Meta-Learning for Sample-Efficient Fine-Tuning of Protein Simulators.
CoRR, 2023

SE(3) Equivalent Graph Attention Network as an Energy-Based Model for Protein Side Chain Conformation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
Accelerated rational PROTAC design via deep learning and molecular simulations.
Nat. Mac. Intell., September, 2022

To Improve Prediction of Binding Residues With DNA, RNA, Carbohydrate, and Peptide Via Multi-Task Deep Neural Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Integrating supercomputing and artificial intelligence for life science.
Patterns, 2022

Quantitative evaluation of explainable graph neural networks for molecular property prediction.
Patterns, 2022

Dynamic graph dropout for subgraph-based relation prediction.
Knowl. Based Syst., 2022

Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction.
J. Chem. Inf. Model., 2022

DRlinker: Deep Reinforcement Learning for Optimization in Fragment Linking Design.
J. Chem. Inf. Model., 2022

AlphaFold2-aware protein-DNA binding site prediction using graph transformer.
Briefings Bioinform., 2022

TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
PharmKG: a dedicated knowledge graph benchmark for bomedical data mining.
Briefings Bioinform., July, 2021

Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Meta Learning for Low-Resource Molecular Optimization.
J. Chem. Inf. Model., 2021

Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches.
J. Chem. Inf. Model., 2021

Deep scaffold hopping with multimodal transformer neural networks.
J. Cheminformatics, 2021

Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map.
J. Cheminformatics, 2021

Molecular Attributes Transfer from Non-Parallel Data.
CoRR, 2021

Learning Attributed Graph Representations with Communicative Message Passing Transformer.
CoRR, 2021

Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction.
CoRR, 2021

BioNavi-NP: Biosynthesis Navigator for Natural Products.
CoRR, 2021

Precise estimation of residue relative solvent accessible area from Cα atom distance matrix using a deep learning method.
Bioinform., 2021

Learning Attributed Graph Representation with Communicative Message Passing Transformer.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

DeepANIS: Predicting antibody paratope from concatenated CDR sequences by integrating bidirectional long-short-term memory and transformer neural networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Communicative Message Passing for Inductive Relation Reasoning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Publisher Correction: Predicting drug-protein interaction using quasi-visual question answering system.
Nat. Mach. Intell., 2020

Predicting drug-protein interaction using quasi-visual question answering system.
Nat. Mach. Intell., 2020

Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks.
J. Chem. Inf. Model., 2020

Predicting the Feasibility of Copper(I)-Catalyzed Alkyne-Azide Cycloaddition Reactions Using a Recurrent Neural Network with a Self-Attention Mechanism.
J. Chem. Inf. Model., 2020

RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Communicative Representation Learning on Attributed Molecular Graphs.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Identifying Structure-Property Relationships through SMILES Syntax Analysis with Self-Attention Mechanism.
J. Chem. Inf. Model., 2019

QBMG: quasi-biogenic molecule generator with deep recurrent neural network.
J. Cheminformatics, 2019

Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks.
CoRR, 2019


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