Wen Zhang

Orcid: 0000-0001-5221-2628

Affiliations:
  • Huazhong Agricultural University, College of Informatics, Wuhan, China (since 2018)
  • Wuhan University, School of Computer Science, China (2009-2018)
  • Wuhan University, School of Computer Science, China (PhD 2009)


According to our database1, Wen Zhang authored at least 80 papers between 2006 and 2024.

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

Timeline

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Bibliography

2024
DeepCRBP: improved predicting function of circRNA-RBP binding sites with deep feature learning.
Frontiers Comput. Sci., April, 2024

A comprehensive review of molecular optimization in artificial intelligence-based drug discovery.
Quant. Biol., 2024

Deep learning for drug-drug interaction prediction: A comprehensive review.
Quant. Biol., 2024

Improving PTM Site Prediction by Coupling of Multi-Granularity Structure and Multi-Scale Sequence Representation.
CoRR, 2024

A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
HimGNN: a novel hierarchical molecular graph representation learning framework for property prediction.
Briefings Bioinform., September, 2023

Enhancing Drug-Drug Interaction Prediction Using Deep Attention Neural Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

DRLM: A Robust Drug Representation Learning Method and its Applications.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

A subcomponent-guided deep learning method for interpretable cancer drug response prediction.
PLoS Comput. Biol., 2023

Multi-view Contrastive Learning Hypergraph Neural Network for Drug-Microbe-Disease Association Prediction.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Multi-Relational Contrastive Learning Graph Neural Network for Drug-Drug Interaction Event Prediction.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Multi-way relation-enhanced hypergraph representation learning for anti-cancer drug synergy prediction.
Bioinform., October, 2022

A Multimodal Framework for Improving in Silico Drug Repositioning With the Prior Knowledge From Knowledge Graphs.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

EPIHC: Improving Enhancer-Promoter Interaction Prediction by Using Hybrid Features and Communicative Learning.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Predicting Coding Potential of RNA Sequences by Solving Local Data Imbalance.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Hierarchical graph representation learning for the prediction of drug-target binding affinity.
Inf. Sci., 2022

Hierarchical Graph Representation Learning for the Prediction of Drug-Target Binding Affinity.
CoRR, 2022

MVGCN: data integration through multi-view graph convolutional network for predicting links in biomedical bipartite networks.
Bioinform., 2022

SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations.
Briefings Bioinform., 2022

A heterogeneous network-based method with attentive meta-path extraction for predicting drug-target interactions.
Briefings Bioinform., 2022

GraphCDR: a graph neural network method with contrastive learning for cancer drug response prediction.
Briefings Bioinform., 2022

PHIAF: prediction of phage-host interactions with GAN-based data augmentation and sequence-based feature fusion.
Briefings Bioinform., 2022

META-DDIE: predicting drug-drug interaction events with few-shot learning.
Briefings Bioinform., 2022

Predicting drug transcriptional response similarity using Signed Graph Convolutional Network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

GMFQP: An Ontology-mediated Gut Microbiota Federated Query Platform.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021
A Fast Linear Neighborhood Similarity-Based Network Link Inference Method to Predict MicroRNA-Disease Associations.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

A spatiotemporal estimation method for hourly rainfall based on F-SVD in the recommender system.
Environ. Model. Softw., 2021

HampDTI: a heterogeneous graph automatic meta-path learning method for drug-target interaction prediction.
CoRR, 2021

Predicting drug-disease associations through layer attention graph convolutional network.
Briefings Bioinform., 2021

ADEIP: an integrated platform of age-dependent expression and immune profiles across human tissues.
Briefings Bioinform., 2021

Tensor decomposition with relational constraints for predicting multiple types of microRNA-disease associations.
Briefings Bioinform., 2021

CSGNN: Contrastive Self-Supervised Graph Neural Network for Molecular Interaction Prediction.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

A Graph-based Approach for Integrating Biological Heterogeneous Data Based on Connecting Ontology.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Predicting Drug-miRNA Resistance with Layer Attention Graph Convolution Network and Multi Channel Feature Extraction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
ncRNA-eQTL: a database to systematically evaluate the effects of SNPs on non-coding RNA expression across cancer types.
Nucleic Acids Res., 2020

Graph embedding and ensemble learning for predicting gene-disease associations.
Int. J. Data Min. Bioinform., 2020

Graph embedding on biomedical networks: methods, applications and evaluations.
Bioinform., 2020

A multimodal deep learning framework for predicting drug-drug interaction events.
Bioinform., 2020

ItLnc-BXE: A Bagging-XGBoost-Ensemble Method With Comprehensive Sequence Features for Identification of Plant lncRNAs.
IEEE Access, 2020

2019
SFLLN: A sparse feature learning ensemble method with linear neighborhood regularization for predicting drug-drug interactions.
Inf. Sci., 2019

Predicting microRNA-disease associations from knowledge graph using tensor decomposition with relational constraints.
CoRR, 2019

A network embedding-based multiple information integration method for the MiRNA-disease association prediction.
BMC Bioinform., 2019

Predicting CircRNA-Disease Associations Through Linear Neighborhood Label Propagation Method.
IEEE Access, 2019

Efficient Network Representations Learning: An Edge-Centric Perspective.
Proceedings of the Knowledge Science, Engineering and Management, 2019

LncRNA-miRNA interaction prediction from the heterogeneous network through graph embedding ensemble learning.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

LncPred-IEL: A Long Non-coding RNA Prediction Method using Iterative Ensemble Learning.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Predicting gene-disease associations from the heterogeneous network using graph embedding.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Detection of Cell Types from Single-cell RNA-seq Data using Similarity via Kernel Preserving Learning Embedding.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Structural Network Embedding using Multi-modal Deep Auto-encoders for Predicting Drug-drug Interactions.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions.
PLoS Comput. Biol., 2018

Manifold regularized matrix factorization for drug-drug interaction prediction.
J. Biomed. Informatics, 2018

The linear neighborhood propagation method for predicting long non-coding RNA-protein interactions.
Neurocomputing, 2018

Feature-derived graph regularized matrix factorization for predicting drug side effects.
Neurocomputing, 2018

Predicting drug-disease associations by using similarity constrained matrix factorization.
BMC Bioinform., 2018

Sequence-based bacterial small RNAs prediction using ensemble learning strategies.
BMC Bioinform., 2018

The Bi-Direction Similarity Integration Method for Predicting Microbe-Disease Associations.
IEEE Access, 2018

Sequence-derived linear neighborhood propagation method for predicting lncRNA-miRNA interactions.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Prediction of Drug-Disease Associations and Their Effects by Signed Network-Based Nonnegative Matrix Factorization.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

HNGRNMF: Heterogeneous Network-based Graph Regularized Nonnegative Matrix Factorization for predicting events of microbe-disease associations.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017
A unified frame of predicting side effects of drugs by using linear neighborhood similarity.
BMC Syst. Biol., 2017

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.
BMC Bioinform., 2017

Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data.
BMC Bioinform., 2017

Predicting drug-disease associations based on the known association bipartite network.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Predicting small RNAs in bacteria via sequence learning ensemble method.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016
Predicting potential side effects of drugs by recommender methods and ensemble learning.
Neurocomputing, 2016

A genetic algorithm-based weighted ensemble method for predicting transposon-derived piRNAs.
BMC Bioinform., 2016

Multi-Domain Manifold Learning for Drug-Target Interaction Prediction.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

The prediction of human splicing branchpoints by multi-label learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Drug side effect prediction through linear neighborhoods and multiple data source integration.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015
Predicting drug side effects by multi-label learning and ensemble learning.
BMC Bioinform., 2015

2013
Predicting immunogenic T-cell epitopes by combining various sequence-derived features.
Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine, 2013

2012
Predicting linear B-cell epitopes by using sequence-derived structural and physicochemical features.
Int. J. Data Min. Bioinform., 2012

2011
Prediction of conformational B-cell epitopes from 3D structures by random forest with a distance-based feature.
BMC Bioinform., 2011

Prediction of Heme Binding Sites in Heme Proteins Using an Integrative Sequence Profile Coupling Evolutionary Information with Physicochemical Properties.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010
Quantitative prediction of MHC-II binding affinity using particle swarm optimization.
Artif. Intell. Medicine, 2010

2009
Quantitative prediction of MHC-II peptide binding affinity using relevance vector machine.
Appl. Intell., 2009

2008
A Bayesian regression approach to the prediction of MHC-II binding affinity.
Comput. Methods Programs Biomed., 2008

Quantitative Prediction of MHC-II Peptide Binding Affinity Using Global Description of Peptide Sequences.
Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics, 2008

2006
Gene Selection Using Rough Set Theory.
Proceedings of the Rough Sets and Knowledge Technology, First International Conference, 2006


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