Zhengwei Li
Orcid: 0000-0003-1644-1006Affiliations:
- University of Mining and Technology, School of Computer Science and Technology, Xuzhou, China
According to our database1,
Zhengwei Li
authored at least 46 papers
between 2008 and 2024.
Collaborative distances:
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Bibliography
2024
Predicting miRNA-Disease Associations Based on Spectral Graph Transformer With Dynamic Attention and Regularization.
IEEE J. Biomed. Health Informatics, December, 2024
BEROLECMI: a novel prediction method to infer circRNA-miRNA interaction from the role definition of molecular attributes and biological networks.
BMC Bioinform., December, 2024
MAGCDA: A Multi-Hop Attention Graph Neural Networks Method for CircRNA-Disease Association Prediction.
IEEE J. Biomed. Health Informatics, March, 2024
GSLCDA: An Unsupervised Deep Graph Structure Learning Method for Predicting CircRNA-Disease Association.
IEEE J. Biomed. Health Informatics, March, 2024
SiSGC: A Drug Repositioning Prediction Model Based on Heterogeneous Simplifying Graph Convolution.
J. Chem. Inf. Model., January, 2024
LMGATCDA: Graph Neural Network With Labeling Trick for Predicting circRNA-Disease Associations.
IEEE ACM Trans. Comput. Biol. Bioinform., 2024
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction.
Briefings Bioinform., 2024
A PiRNA-disease association model incorporating sequence multi-source information with graph convolutional networks.
Appl. Soft Comput., 2024
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024
Predicting CircRNA-Disease Associations Through Non-negative Matrix Factorization and Adversarially Regularized Variational Graph Autoencoder.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
2023
An efficient circRNA-miRNA interaction prediction model by combining biological text mining and wavelet diffusion-based sparse network structure embedding.
Comput. Biol. Medicine, October, 2023
Bioinform., February, 2023
SPRDA: a link prediction approach based on the structural perturbation to infer disease-associated Piwi-interacting RNAs.
Briefings Bioinform., January, 2023
Predicting Mirna-Disease Associations Based on Neighbor Selection Graph Attention Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
Predicting MiRNA-Disease Associations by Graph Representation Learning Based on Jumping Knowledge Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
ADARES: A Single-cell Classification Model Based on Adversarial Data Augmentation and Residual Networks.
Proceedings of the 6th International Conference on Signal Processing and Machine Learning, 2023
A Graph Neural Network with Multiple Auxiliary Tasks for Accurate Single Cell Classification.
Proceedings of the 6th International Conference on Signal Processing and Machine Learning, 2023
2022
GCMCDTI: Graph convolutional autoencoder framework for predicting drug-target interactions based on matrix completion.
J. Bioinform. Comput. Biol., 2022
Predicting miRNA-disease associations based on graph random propagation network and attention network.
Briefings Bioinform., 2022
iGRLCDA: identifying circRNA-disease association based on graph representation learning.
Briefings Bioinform., 2022
A machine learning framework based on multi-source feature fusion for circRNA-disease association prediction.
Briefings Bioinform., 2022
Prediction of MiRNA-Disease Association Based on Higher-Order Graph Convolutional Networks.
Proceedings of the Intelligent Computing Theories and Application, 2022
Research on the Potential Mechanism of Rhizoma Drynariae in the Treatment of Periodontitis Based on Network Pharmacology.
Proceedings of the Intelligent Computing Theories and Application, 2022
Proceedings of the Intelligent Computing Theories and Application, 2022
The Prognosis Model of Clear Cell Renal Cell Carcinoma Based on Allograft Rejection Markers.
Proceedings of the Intelligent Computing Theories and Application, 2022
Elucidating Quantum Semi-empirical Based QSAR, for Predicting Tannins' Anti-oxidant Activity with the Help of Artificial Neural Network.
Proceedings of the Intelligent Computing Theories and Application, 2022
2021
Efficient framework for predicting MiRNA-disease associations based on improved hybrid collaborative filtering.
BMC Medical Informatics Decis. Mak., 2021
BMC Bioinform., 2021
Briefings Bioinform., 2021
Delineating QSAR Descriptors to Explore the Inherent Properties of Naturally Occurring Polyphenols, Responsible for Alpha-Synuclein Amyloid Disaggregation Scheming Towards Effective Therapeutics Against Parkinson's Disorder.
Proceedings of the Intelligent Computing Theories and Application, 2021
Study on the Mechanism of Cistanche in the Treatment of Colorectal Cancer Based on Network Pharmacology.
Proceedings of the Intelligent Computing Theories and Application, 2021
2020
Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model.
BMC Bioinform., 2020
Proceedings of the Intelligent Computing Theories and Application, 2020
GCNSP: A Novel Prediction Method of Self-Interacting Proteins Based on Graph Convolutional Networks.
Proceedings of the Intelligent Computing Theories and Application, 2020
Expression and Gene Regulation Network of ELF3 in Breast Invasive Carcinoma Based on Data Mining.
Proceedings of the Intelligent Computing Theories and Application, 2020
A Network Embedding-Based Method for Predicting miRNA-Disease Associations by Integrating Multiple Information.
Proceedings of the Intelligent Computing Methodologies - 16th International Conference, 2020
2019
Prediction of potential miRNA-disease associations using matrix decomposition and label propagation.
Knowl. Based Syst., 2019
Using discriminative vector machine model with 2DPCA to predict interactions among proteins.
BMC Bioinform., 2019
An Efficient LightGBM Model to Predict Protein Self-interacting Using Chebyshev Moments and Bi-gram.
Proceedings of the Intelligent Computing Theories and Application, 2019
LRMDA: Using Logistic Regression and Random Walk with Restart for MiRNA-Disease Association Prediction.
Proceedings of the Intelligent Computing Theories and Application, 2019
Proceedings of the Intelligent Computing Theories and Application, 2019
2018
Efficient Framework for Predicting ncRNA-Protein Interactions Based on Sequence Information by Deep Learning.
Proceedings of the Intelligent Computing Theories and Application, 2018
2017
PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.
PLoS Comput. Biol., 2017
2012
J. Softw., 2012
2010
Proceedings of the Sixth International Conference on Natural Computation, 2010
2008
Proceedings of the Fourth International Conference on Natural Computation, 2008