Yuedong Yang
Orcid: 0000-0002-6782-2813
According to our database1,
Yuedong Yang
authored at least 124 papers
between 2006 and 2024.
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Bibliography
2024
An uncertainty-based interpretable deep learning framework for predicting breast cancer outcome.
BMC Bioinform., December, 2024
Predicting the effects of mutations on protein solubility using graph convolution network and protein language model representation.
J. Comput. Chem., March, 2024
Predicting disease-gene associations through self-supervised mutual infomax graph convolution network.
Comput. Biol. Medicine, March, 2024
GRELinker: A Graph-Based Generative Model for Molecular Linker Design with Reinforcement and Curriculum Learning.
J. Chem. Inf. Model., 2024
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks.
CoRR, 2024
2023
IEEE Trans. Computers, November, 2023
Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering.
Briefings Bioinform., November, 2023
Briefings Bioinform., November, 2023
Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization.
NeuroImage, October, 2023
ShockSurv: A machine learning model to accurately predict 28-day mortality for septic shock patients in the intensive care unit.
Biomed. Signal Process. Control., September, 2023
Accurately identifying nucleic-acid-binding sites through geometric graph learning on language model predicted structures.
Briefings Bioinform., September, 2023
Fast and accurate protein intrinsic disorder prediction by using a pretrained language model.
Briefings Bioinform., July, 2023
IEEE Trans. Knowl. Data Eng., June, 2023
Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion.
Briefings Bioinform., May, 2023
Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model.
Bioinform., April, 2023
Identifying spatial domain by adapting transcriptomics with histology through contrastive learning.
Briefings Bioinform., March, 2023
EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning.
Briefings Bioinform., January, 2023
Onboard Sensors-Based Self-Localization for Autonomous Vehicle With Hierarchical Map.
IEEE Trans. Cybern., 2023
A Drug Combination Prediction Framework Based on Graph Convolutional Network and Heterogeneous Information.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Accurately Identifying Muscle-Invasive Bladder Cancer from MRI via Weakly Supervised Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 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
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
Patterns, 2022
Quantitative evaluation of explainable graph neural networks for molecular property prediction.
Patterns, 2022
tsRFun: a comprehensive platform for decoding human tsRNA expression, functions and prognostic value by high-throughput small RNA-Seq and CLIP-Seq data.
Nucleic Acids Res., 2022
Knowl. Based Syst., 2022
J. Comput. Sci. Technol., 2022
J. Chem. Inf. Model., 2022
J. Chem. Inf. Model., 2022
IET Image Process., 2022
CoRR, 2022
Comput. Biol. Medicine, 2022
Briefings Bioinform., 2022
Spatial transcriptomics prediction from histology jointly through Transformer and graph neural networks.
Briefings Bioinform., 2022
Briefings Bioinform., 2022
Alignment-free metal ion-binding site prediction from protein sequence through pretrained language model and multi-task learning.
Briefings Bioinform., 2022
Briefings Bioinform., 2022
Capturing large genomic contexts for accurately predicting enhancer-promoter interactions.
Briefings Bioinform., 2022
A Multi-constraint Deep Semi-supervised Learning Method for Ovarian Cancer Prognosis Prediction.
Proceedings of the Advances in Swarm Intelligence - 13th International Conference, 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
SCdenoise: a reference-based scRNA-seq denoising method using semi-supervised learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
Genetic and phenotypic relationships between coronary atherosclerotic heart disease and electrocardiographic traits.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
Accurately Identifying Coronary Atherosclerotic Heart Disease through Merged Beats of Electrocardiogram.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
A Meta-learning based Graph-Hierarchical Clustering Method for Single Cell RNA-Seq Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
Briefings Bioinform., July, 2021
Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Exploring complex and heterogeneous correlations on hypergraph for the prediction of drug-target interactions.
Patterns, 2021
EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput experiments.
Nucleic Acids Res., 2021
J. Cheminformatics, 2021
Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map.
J. Cheminformatics, 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
Predicting bladder cancer prognosis by integrating multi-omics data through a transfer learning-based Cox proportional hazards network.
CCF Trans. High Perform. Comput., 2021
Integrating multi-omics data through deep learning for accurate cancer prognosis prediction.
Comput. Biol. Medicine, 2021
Structure-aware protein-protein interaction site prediction using deep graph convolutional network.
Bioinform., 2021
scAdapt: virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species.
Briefings Bioinform., 2021
Integration of Patch Features Through Self-supervised Learning and Transformer for Survival Analysis on Whole Slide Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Learning Attributed Graph Representation with Communicative Message Passing Transformer.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Anytime Depth Estimation with Limited Sensing and Computation Capabilities on Mobile Devices.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 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
DGAT-onco: A differential analysis method to detect oncogenes by integrating functional information of mutations.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
SEGEM: a Fast and Accurate Automated Protein Backbone Structure Modeling Method for Cryo-EM.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
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
Nat. Mach. Intell., 2020
Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks.
J. Chem. Inf. Model., 2020
Accurately Predicting Mutation-Caused Stability Changes from Protein Sequences Using Extreme Gradient Boosting.
J. Chem. Inf. Model., 2020
To Improve Protein Sequence Profile Prediction through Image Captioning on Pairwise Residue Distance Map.
J. Chem. Inf. Model., 2020
SPOT-Fold: Fragment-Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map.
J. Comput. Chem., 2020
All-Atom Knowledge-Based Potential for RNA Structure Discrimination Based on the Distance-Scaled Finite Ideal-Gas Reference State.
J. Comput. Biol., 2020
Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning.
J. Comput. Biol., 2020
Accurate prediction of genome-wide RNA secondary structure profile based on extreme gradient boosting.
Bioinform., 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 46th Annual Conference of the IEEE Industrial Electronics Society, 2020
Accurately Clustering Single-cell RNA-seq data by Capturing Structural Relations between Cells through Graph Convolutional Network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
Identifying Structure-Property Relationships through SMILES Syntax Analysis with Self-Attention Mechanism.
J. Chem. Inf. Model., 2019
SPOT-Peptide: Template-Based Prediction of Peptide-Binding Proteins and Peptide-Binding Sites.
J. Chem. Inf. Model., 2019
J. Cheminformatics, 2019
DLIGAND2: an improved knowledge-based energy function for protein-ligand interactions using the distance-scaled, finite, ideal-gas reference state.
J. Cheminformatics, 2019
CoRR, 2019
Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks.
Bioinform., 2019
2018
EVLncRNAs: a manually curated database for long non-coding RNAs validated by low-throughput experiments.
Nucleic Acids Res., 2018
Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning.
J. Chem. Inf. Model., 2018
Predicting lysine-malonylation sites of proteins using sequence and predicted structural features.
J. Comput. Chem., 2018
Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning.
J. Comput. Chem., 2018
<i>B</i>-factor profile prediction for RNA flexibility using support vector machines.
J. Comput. Chem., 2018
Grid-based prediction of torsion angle probabilities of protein backbone and its application to discrimination of protein intrinsic disorder regions and selection of model structures.
BMC Bioinform., 2018
Bioinform., 2018
Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.
Bioinform., 2018
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Briefings Bioinform., 2018
2017
J. Comb. Optim., 2017
LRFragLib: an effective algorithm to identify fragments for de novo protein structure prediction.
Bioinform., 2017
SPOT-ligand 2: improving structure-based virtual screening by binding-homology search on an expanded structural template library.
Bioinform., 2017
Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility.
Bioinform., 2017
Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.
Bioinform., 2017
2016
Sequence-Based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines.
J. Chem. Inf. Model., 2016
SPOT-Ligand: Fast and effective structure-based virtual screening by binding homology search according to ligand and receptor similarity.
J. Comput. Chem., 2016
J. Comput. Chem., 2016
Sequence-based prediction of protein-peptide binding sites using support vector machine.
J. Comput. Chem., 2016
sDFIRE: Sequence-specific statistical energy function for protein structure prediction by decoy selections.
J. Comput. Chem., 2016
Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins.
Bioinform., 2016
Predicting the errors of predicted local backbone angles and non-local solvent- accessibilities of proteins by deep neural networks.
Bioinform., 2016
Fast and accurate non-sequential protein structure alignment using a new asymmetric linear sum assignment heuristic.
Bioinform., 2016
2015
DDIG-in: detecting disease-causing genetic variations due to frameshifting indels and nonsense mutations employing sequence and structural properties at nucleotide and protein levels.
Bioinform., 2015
2014
Carbohydrate-binding protein identification by coupling structural similarity searching with binding affinity prediction.
J. Comput. Chem., 2014
Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.
J. Comput. Chem., 2014
2012
SPINE X: Improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles.
J. Comput. Chem., 2012
2011
Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates.
Bioinform., 2011
2010
Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function.
Bioinform., 2010
2008
Proceedings of the 1st ACM SIGMM International Conference on Multimedia Information Retrieval, 2008
DTW-Curve for Classification of Logically Similar Motions.
Proceedings of the GRAPP 2008, 2008
2006
Genetic algorithms for protein conformation sampling and optimization in a discrete backbone dihedral angle space.
J. Comput. Chem., 2006