Jing Hu

Orcid: 0000-0003-1348-8773

Affiliations:
  • Wuhan University of Science and Technology, School of Computer Science and Technology, China


According to our database1, Jing Hu authored at least 25 papers between 2015 and 2024.

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

Timeline

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Bibliography

2024
Drug Molecule Generation Method Based on Fusion of Protein Sequence Features.
Proceedings of the Advanced Intelligent Computing in Bioinformatics, 2024

Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism.
Proceedings of the Advanced Intelligent Computing in Bioinformatics, 2024

Drug Target Affinity Prediction Based on Graph Structural Enhancement and Multi-scale Topological Feature Fusion.
Proceedings of the Advanced Intelligent Computing in Bioinformatics, 2024

2023
Drug-Target Affinity Prediction Based on Self-attention Graph Pooling and Mutual Interaction Neural Network.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

Identifying Drug-Target Interactions Through a Combined Graph Attention Mechanism and Self-attention Sequence Embedding Model.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

An Efficient Drug Design Method Based on Drug-Target Affinity.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

De Novo Drug Design Using Unified Multilayer Simple Recurrent Unit Model.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

DU-DANet: Efficient 3D Automatic Brain Tumor Segmentation Based on Dual Attention.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

Drug-Target Interaction Prediction Based on Drug Subgraph Fingerprint Extraction Strategy and Subgraph Attention Mechanism.
Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023

2022
Unsupervised Prediction Method for Drug-Target Interactions Based on Structural Similarity.
Proceedings of the Intelligent Computing Theories and Application, 2022

Drug-Target Affinity Prediction Based on Multi-channel Graph Convolution.
Proceedings of the Intelligent Computing Theories and Application, 2022

Drug-Target Binding Affinity Prediction Based on Graph Neural Networks and Word2vec.
Proceedings of the Intelligent Computing Theories and Application, 2022

2021
Improve hot region prediction by analyzing different machine learning algorithms.
BMC Bioinform., 2021

Prediction of hot spots in protein-protein interaction by Nine-Pipeline & Ensemble Learning strategy.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
Identification of protein hot regions by combining structure-based classification, energy-based clustering and sequence-based conservation in evolution.
Int. J. Data Min. Bioinform., 2020

2019
Improving Hot Region Prediction by Combining Gaussian Naive Bayes and DBSCAN.
Proceedings of the Intelligent Computing Theories and Application, 2019

Identification of protein hot regions by integrated machine learning algorithm.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
Accurate Prediction of Hot Spots with Greedy Gradient Boosting Decision Tree.
Proceedings of the Intelligent Computing Theories and Application, 2018

Analysis of hot regions prediction in PPI with different amino acid mutation using machine learning algorithm.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017
Classification of Hub Protein and Analysis of Hot Regions in Protein-Protein Interactions.
Proceedings of the Intelligent Computing Theories and Application, 2017

Protein Hot Regions Feature Research Based on Evolutionary Conservation.
Proceedings of the Intelligent Computing Theories and Application, 2017

2015
Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification.
Comput. Biol. Medicine, 2015

Identification of Hot Regions in Protein Interfaces: Combining Density Clustering and Neighbor Residues Improves the Accuracy.
Proceedings of the Intelligent Computing Theories and Methodologies, 2015

Testing whether hot regions in protein-protein interactions are conserved in different species.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

Prediction of hot regions in protein-protein interaction by density-based incremental clustering with parameter selection.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015


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