Yuedong Yang

Orcid: 0000-0002-6782-2813

According to our database1, Yuedong Yang authored at least 129 papers between 2006 and 2024.

Collaborative distances:



In proceedings 
PhD thesis 


On csauthors.net:


An uncertainty-based interpretable deep learning framework for predicting breast cancer outcome.
BMC Bioinform., December, 2024

Deciphering cell types by integrating scATAC-seq data with genome sequences.
Nat. Comput. Sci., April, 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

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

DiffDec: Structure-Aware Scaffold Decoration with an End-to-End Diffusion Model.
J. Chem. Inf. Model., 2024

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

Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma.
Comput. Biol. Medicine, 2024

Self-supervised learning on millions of primary RNA sequences from 72 vertebrates improves sequence-based RNA splicing prediction.
Briefings Bioinform., 2024

SUGAR: Efficient Subgraph-Level Training via Resource-Aware Graph Partitioning.
IEEE Trans. Computers, November, 2023

Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering.
Briefings Bioinform., November, 2023

From intuition to AI: evolution of small molecule representations in drug discovery.
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

Subgraph-Aware Few-Shot Inductive Link Prediction Via Meta-Learning.
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

Node-based Knowledge Graph Contrastive Learning for Medical Relationship Prediction.
CoRR, 2023

Efficient Low-rank Backpropagation for Vision Transformer Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Retrieval-based Knowledge Augmented Vision Language Pre-training.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

TIPS: Topologically Important Path Sampling for Anytime Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

ZiCo: Zero-shot NAS via inverse Coefficient of Variation on Gradients.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient On-Device Training via Gradient Filtering.
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

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

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

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

Imputing DNA Methylation by Transferred Learning Based Neural Network.
J. Comput. Sci. Technol., 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

A coarse-refine segmentation network for COVID-19 CT images.
IET Image Process., 2022

SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning.
CoRR, 2022

Cancer survival prognosis with Deep Bayesian Perturbation Cox Network.
Comput. Biol. Medicine, 2022

A parameter-free deep embedded clustering method for single-cell RNA-seq data.
Briefings Bioinform., 2022

Spatial transcriptomics prediction from histology jointly through Transformer and graph neural networks.
Briefings Bioinform., 2022

A robust and scalable graph neural network for accurate single-cell classification.
Briefings Bioinform., 2022

Alignment-free metal ion-binding site prediction from protein sequence through pretrained language model and multi-task learning.
Briefings Bioinform., 2022

AlphaFold2-aware protein-DNA binding site prediction using graph transformer.
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

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

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

Meta Learning for Low-Resource Molecular Optimization.
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

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

Multi-omics Cancer Prognosis Analysis Based on Graph Convolution Network.
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

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

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

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

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

HeLPS: Heterogeneous LiDAR-based Positioning System for Autonomous Vehicle.
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

An End-to-end Oxford Nanopore Basecaller Using Convolution-augmented Transformer.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

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

QBMG: quasi-biogenic molecule generator with deep recurrent neural network.
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

Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks.
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

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

Structure-based prediction of protein- peptide binding regions using Random Forest.
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

A heuristic for the time constrained asymmetric linear sum assignment problem.
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

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

Effective protein conformational sampling based on predicted torsion angles.
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

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

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

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

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

Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function.
Bioinform., 2010

View-invariant action recognition using interest points.
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

Genetic algorithms for protein conformation sampling and optimization in a discrete backbone dihedral angle space.
J. Comput. Chem., 2006