Min Zeng
Orcid: 0000-0002-1726-0955Affiliations:
- Central South University, Changsha, China
According to our database1,
Min Zeng
authored at least 51 papers
between 2018 and 2025.
Collaborative distances:
Collaborative distances:
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on orcid.org
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Bibliography
2025
GateFuseNet: An Adaptive 3D Multimodal Neuroimaging Fusion Network for Parkinson's Disease Diagnosis.
CoRR, October, 2025
CoRR, October, 2025
Contrastive Regularization over LoRA for Multimodal Biomedical Image Incremental Learning.
CoRR, August, 2025
CellCircLoc: Deep Neural Network for Predicting and Explaining Cell Line-Specific CircRNA Subcellular Localization.
IEEE J. Biomed. Health Informatics, February, 2025
DDLB: Using the Protein Language Model and Hierarchical Architecture to Improve Disordered Lipid-Binding Residues Prediction.
Proceedings of the Bioinformatics Research and Applications - 21st International Symposium, 2025
2024
Rapid screening of multi-point mutations for enzyme thermostability modification by utilizing computational tools.
Future Gener. Comput. Syst., 2024
SGCL-LncLoc: An Interpretable Deep Learning Model for Improving IncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning.
Big Data Min. Anal., 2024
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches.
Briefings Bioinform., 2024
Aligning Multimodal Biomedical Images and Language via One Large Vision-Language Model.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
ComLMEss: Combining multiple protein language models enables accurate essential protein prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
DP-BERT: a pre-trained deep language model for depression prediction using microarray data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
2023
LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism.
Bioinform., December, 2023
ViPal: A framework for virulence prediction of influenza viruses with prior viral knowledge using genomic sequences.
J. Biomed. Informatics, June, 2023
Briefings Bioinform., May, 2023
DeepCellEss: cell line-specific essential protein prediction with attention-based interpretable deep learning.
Bioinform., January, 2023
CRMSS: predicting circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features.
Briefings Bioinform., January, 2023
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network.
Briefings Bioinform., January, 2023
GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation.
Briefings Bioinform., January, 2023
A Deep Learning Framework for Predicting Protein Functions With Co-Occurrence of GO Terms.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
Singularformer: Learning to Decompose Self-Attention to Linearize the Complexity of Transformer.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Protein function prediction using graph neural network with multi-type biological knowledge.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
2022
IEEE J. Biomed. Health Informatics, 2022
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
Neurocomputing, 2022
Bioinform., 2022
DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding.
Briefings Bioinform., 2022
A framework for predicting variable-length epitopes of human-adapted viruses using machine learning methods.
Briefings Bioinform., 2022
ASNet: An Adversarial Sparse Network for Multi-task Biomedical Named Entity Recognition.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
LDAGSO: Predicting 1ncRNA-Disease Associations from Graph Sequences and Disease Ontology via Deep Learning techniques.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
IEEE J. Biomed. Health Informatics, 2021
A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Neurocomputing, 2021
CoRR, 2021
Improving circRNA-disease association prediction by sequence and ontology representations with convolutional and recurrent neural networks.
Bioinform., 2021
Improving human essential protein prediction using only protein sequences via ensemble learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
BMC Bioinform., 2020
PROBselect: accurate prediction of protein-binding residues from proteins sequences via dynamic predictor selection.
Bioinform., 2020
Protein-protein interaction site prediction through combining local and global features with deep neural networks.
Bioinform., 2020
Briefings Bioinform., 2020
Ess-NEXG: Predict Essential Proteins by Constructing a Weighted Protein Interaction Network Based on Node Embedding and XGBoost.
Proceedings of the Bioinformatics Research and Applications - 16th International Symposium, 2020
2019
IEEE ACM Trans. Comput. Biol. Bioinform., 2019
BMC Bioinform., 2019
LncRNA-disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
HNEDTI: Prediction of drug-target interaction based on heterogeneous network embedding.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
2018
A Deep Learning Framework for Identifying Essential Proteins Based on Protein-Protein Interaction Network and Gene Expression Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018