Lei Deng

Orcid: 0000-0003-2869-1619

Affiliations:
  • Central South University, School of Software, Changsha, China


According to our database1, Lei Deng authored at least 70 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
MSF-PFP: A Novel Multisource Feature Fusion Model for Protein Function Prediction.
J. Chem. Inf. Model., March, 2024

AntiViralDL: Computational Antiviral Drug Repurposing Using Graph Neural Network and Self-Supervised Learning.
IEEE J. Biomed. Health Informatics, January, 2024

2023
Large-scale predicting protein functions through heterogeneous feature fusion.
Briefings Bioinform., July, 2023

Prediction of circRNA-MiRNA Association Using Singular Value Decomposition and Graph Neural Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

NGCICM: A Novel Deep Learning-Based Method for Predicting circRNA-miRNA Interactions.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

HGNNLDA: Predicting lncRNA-Drug Sensitivity Associations via a Dual Channel Hypergraph Neural Network.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

GCNPCA: miRNA-Disease Associations Prediction Algorithm Based on Graph Convolutional Neural Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

DeepCoVDR: deep transfer learning with graph transformer and cross-attention for predicting COVID-19 drug response.
Bioinform., 2023

PTDA-SWGCL: Predicting tRNA-Disease Associations using Supplementarily Weighted Graph Contrastive Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Predicting Associations between circRNAs and Drug Sensitivity using Heterogeneous Graphs and Graph Attention Networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

TGC-ARG: Predicting Antibiotic Resistance through Transformer-based Modeling and Contrastive Learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Enhancing Protein Solubility Prediction through Pre-trained Language Models and Graph Convolutional Neural Networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
MGATMDA: Predicting Microbe-Disease Associations via Multi-Component Graph Attention Network.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

MSCNE: Predict miRNA-Disease Associations Using Neural Network Based on Multi-Source Biological Information.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Graph Neural Network with Self-Supervised Learning for Noncoding RNA-Drug Resistance Association Prediction.
J. Chem. Inf. Model., 2022

Dual-Channel Heterogeneous Graph Neural Network for Predicting microRNA-Mediated Drug Sensitivity.
J. Chem. Inf. Model., 2022

Predicting circRNA-drug sensitivity associations via graph attention auto-encoder.
BMC Bioinform., 2022

MSPCD: predicting circRNA-disease associations via integrating multi-source data and hierarchical neural network.
BMC Bioinform., 2022

Graph2MDA: a multi-modal variational graph embedding model for predicting microbe-drug associations.
Bioinform., 2022

Computational anti-COVID-19 drug design: progress and challenges.
Briefings Bioinform., 2022

DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations.
Briefings Bioinform., 2022

TSNAPred: predicting type-specific nucleic acid binding residues via an ensemble approach.
Briefings Bioinform., 2022

Attention-wise masked graph contrastive learning for predicting molecular property.
Briefings Bioinform., 2022

Contrastive learning-based computational histopathology predict differential expression of cancer driver genes.
Briefings Bioinform., 2022

inACP: An integrated approach to the prediction of anticancer peptides.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

DeepFusionGO: Protein function prediction by fusing heterogeneous features through deep learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021
LDAH2V: Exploring Meta-Paths Across Multiple Networks for lncRNA-Disease Association Prediction.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

MSCFS: inferring circRNA functional similarity based on multiple data sources.
BMC Bioinform., 2021

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network.
BMC Bioinform., 2021

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost.
BMC Bioinform., 2021

Nabe: an energetic database of amino acid mutations in protein-nucleic acid binding interfaces.
Database J. Biol. Databases Curation, 2021

LGCMDS: Predicting miRNA-Drug Sensitivity based on Light Graph Convolution Network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Accurately Predicting circRNA-disease Associations Using Variational Graph Auto-encoders and LightGBM.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

CMIVGSD: circRNA-miRNA Interaction Prediction Based on Variational Graph Auto-Encoder and Singular Value Decomposition.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

iPiDA-GBNN: Identification of Piwi-interacting RNA-disease associations based on gradient boosting neural network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

GCNSDA: Predicting snoRNA-disease associations via graph convolutional network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

A multi-task graph convolutional network modeling of drug-drug interactions and synergistic efficacy.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
DrugCombDB: a comprehensive database of drug combinations toward the discovery of combinatorial therapy.
Nucleic Acids Res., 2020

HNet-DNN: Inferring New Drug-Disease Associations with Deep Neural Network Based on Heterogeneous Network Features.
J. Chem. Inf. Model., 2020

Pathway-Guided Deep Neural Network toward Interpretable and Predictive Modeling of Drug Sensitivity.
J. Chem. Inf. Model., 2020

Gammachirp filter banks applied in roust speaker recognition based on GMM-UBM classifier.
Int. Arab J. Inf. Technol., 2020

DeepciRGO: functional prediction of circular RNAs through hierarchical deep neural networks using heterogeneous network features.
BMC Bioinform., 2020

Machine learning-based methods and novel data models to predict adverse drug reaction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Predict the Protein-protein Interaction between Virus and Host through Hybrid Deep Neural Network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

DeepARC: An Attention-based Hybrid Model for Predicting Transcription Factor Binding Sites from Positional Embedded DNA Sequence.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Predicting circRNA-disease associations using meta path-based representation learning on heterogenous network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019
KATZLGO: Large-Scale Prediction of LncRNA Functions by Using the KATZ Measure Based on Multiple Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019

Integrating Multiple Heterogeneous Networks for Novel LncRNA-Disease Association Inference.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019

MultiSourcDSim: an integrated approach for exploring disease similarity.
BMC Medical Informatics Decis. Mak., 2019

MADOKA: an ultra-fast approach for large-scale protein structure similarity searching.
BMC Bioinform., 2019

D2VCB: A Hybrid Deep Neural Network for the Prediction of in-vivo Protein-DNA Binding from Combined DNA Sequence.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

DKCirc2GO: Predicting Gene Ontology of circRNAs Using Dual KATZ Approach.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

A deep neural network approach using distributed representations of RNA sequence and structure for identifying binding site of RNA-binding proteins.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
Probing the functions of long non-coding RNAs by exploiting the topology of global association and interaction network.
Comput. Biol. Chem., 2018

PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine.
BMC Bioinform., 2018

Ontological function annotation of long non-coding RNAs through hierarchical multi-label classification.
Bioinform., 2018

XPredRBR: Accurate and Fast Prediction of RNA-Binding Residues in Proteins Using eXtreme Gradient Boosting.
Proceedings of the Bioinformatics Research and Applications - 14th International Symposium, 2018

Exploring Disease Similarity by Integrating Multiple Data Sources.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017
A boosting approach for prediction of protein-RNA binding residues.
BMC Bioinform., 2017

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction.
BMC Bioinform., 2017

BiRWLGO: A global network-based strategy for lncRNA function annotation using bi-random walk.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016
PredRSA: a gradient boosted regression trees approach for predicting protein solvent accessibility.
BMC Bioinform., 2016

PredRBR: Accurate Prediction of RNA-Binding Residues in proteins using Gradient Tree Boosting.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015
An Integrated Framework for Functional Annotation of Protein Structural Domains.
IEEE ACM Trans. Comput. Biol. Bioinform., 2015

2014
PredHS: a web server for predicting protein-protein interaction hot spots by using structural neighborhood properties.
Nucleic Acids Res., 2014

A Multi-Instance Multi-Label Learning Approach for Protein Domain Annotation.
Proceedings of the Intelligent Computing in Bioinformatics - 10th International Conference, 2014

Structure-Based Prediction of Protein Phosphorylation Sites Using an Ensemble Approach.
Proceedings of the Intelligent Computing in Bioinformatics - 10th International Conference, 2014

2013
PrePPI: a structure-informed database of protein-protein interactions.
Nucleic Acids Res., 2013

Boosting Prediction Performance of Protein-Protein Interaction Hot Spots by Using Structural Neighborhood Properties.
J. Comput. Biol., 2013

2011
PredUs: a web server for predicting protein interfaces using structural neighbors.
Nucleic Acids Res., 2011


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