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ORCIDJing Hu 0003
Person information
- affiliation: Wuhan University of Science and Technology, School of Computer Science and Technology, China
Other persons with the same name
- Jing Hu — disambiguation page
- Jing Hu 0001 — Utah State University, Department of Computer Science, Logan, UT, USA
- Jing Hu 0002
![[0000-0001-8618-5533]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0001-8618-5533")
— Southeast University, National Mobile Communications Research Laboratory, Nanjing, China - Jing Hu 0004 — Beijing Forestry University, School of Information Science and Technology, China (and 1 more)
- Jing Hu 0005 — Xi'an University of Technology, Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, China (and 1 more)
- Jing Hu 0006 — University of Birmingham, UK
- Jing Hu 0007 — Tianjin University, School of Computer Science and Technology, China
- Jing Hu 0008 — Jinan University, First Affiliated Hospital, Department of Acupuncture and Moxibustion, Guangzhou, China
- Jing Hu 0009 — Chengdu University of Information Technology, Department of Computer Science,China (and 1 more)
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2020 – today
- 2024
[c22]Mengyao Wang, Xiaolong Zhang, Haoran Liu, Xiaoli Lin, Jing Hu, Jun Pang:
Drug Molecule Generation Method Based on Fusion of Protein Sequence Features. ICIC (LNBI 2) 2024: 119-130- [c21]Shuo Hu, Jing Hu, Xiaolong Zhang:
Drug Target Affinity Prediction Based on Graph Structural Enhancement and Multi-scale Topological Feature Fusion. ICIC (LNBI 2) 2024: 131-142 - [c20]Weiwenzheng Liu, Xiaolong Zhang, Xiaoli Lin, Jing Hu:
Drug-Target Interaction Prediction Based on Multi-path Graph Convolution and Graph-Level Attention Mechanism. ICIC (LNBI 2) 2024: 143-154 - 2023
- [c19]Lizhi Wang, Xiaolong Zhang, Xiaoli Lin, Jing Hu:
Drug-Target Interaction Prediction Based on Drug Subgraph Fingerprint Extraction Strategy and Subgraph Attention Mechanism. ADMA (3) 2023: 3-17 - [c18]Kang Wang, Jing Hu, Xiaolong Zhang:
Identifying Drug-Target Interactions Through a Combined Graph Attention Mechanism and Self-attention Sequence Embedding Model. ICIC (3) 2023: 246-257 - [c17]Zonghao Li, Jing Hu, Xiaolong Zhang:
De Novo Drug Design Using Unified Multilayer Simple Recurrent Unit Model. ICIC (3) 2023: 627-638 - [c16]Haoran Liu, Xiaolong Zhang, Xiaoli Lin, Jing Hu:
An Efficient Drug Design Method Based on Drug-Target Affinity. ICIC (3) 2023: 764-775 - [c15]Xizi Wang, Jing Hu, Xiaolong Zhang:
Drug-Target Affinity Prediction Based on Self-attention Graph Pooling and Mutual Interaction Neural Network. ICIC (3) 2023: 776-790 - [c14]Zhenhua Cai, Xiaoli Lin, Xiaolong Zhang, Jing Hu:
DU-DANet: Efficient 3D Automatic Brain Tumor Segmentation Based on Dual Attention. ICIC (3) 2023: 791-802 - 2022
- [c13]Minghao Xia, Jing Hu, Xiaolong Zhang, Xiaoli Lin:
Drug-Target Binding Affinity Prediction Based on Graph Neural Networks and Word2vec. ICIC (2) 2022: 496-506 - [c12]Xinyuan Zhang, Xiaoli Lin, Jing Hu, Wenquan Ding:
Unsupervised Prediction Method for Drug-Target Interactions Based on Structural Similarity. ICIC (2) 2022: 517-532 - [c11]Hang Zhang, Jing Hu, Xiaolong Zhang:
Drug-Target Affinity Prediction Based on Multi-channel Graph Convolution. ICIC (2) 2022: 533-546 - 2021
- [j3]Jing Hu, Longwei Zhou, Bo Li, Xiaolong Zhang, Nansheng Chen:
Improve hot region prediction by analyzing different machine learning algorithms. BMC Bioinform. 22(3): 522 (2021) - [c10]Jing Hu, Zonghao Li, Xiaolong Zhang, Nansheng Chen:
Prediction of hot spots in protein-protein interaction by Nine-Pipeline & Ensemble Learning strategy. BIBM 2021: 2223-2230 - 2020
- [j2]Jing Hu, Haomin Gan, Nansheng Chen, Xiaolong Zhang:
Identification of protein hot regions by combining structure-based classification, energy-based clustering and sequence-based conservation in evolution. Int. J. Data Min. Bioinform. 24(1): 74-95 (2020)
2010 – 2019
- 2019
- [c9]Jing Hu, Haomin Gan, Xiaolong Zhang, Nansheng Chen:
Identification of protein hot regions by integrated machine learning algorithm. BIBM 2019: 24-29 - [c8]Jing Hu, Longwei Zhou, Xiaolong Zhang, Nansheng Chen:
Improving Hot Region Prediction by Combining Gaussian Naive Bayes and DBSCAN. ICIC (2) 2019: 440-452 - 2018
- [c7]Jing Hu, Haomin Gan, Xiaolong Zhang, Nansheng Chen:
Analysis of hot regions prediction in PPI with different amino acid mutation using machine learning algorithm. BIBM 2018: 2254-2261 - [c6]Haomin Gan, Jing Hu, Xiaolong Zhang, Qianqian Huang, Jiafu Zhao:
Accurate Prediction of Hot Spots with Greedy Gradient Boosting Decision Tree. ICIC (2) 2018: 353-364 - 2017
- [c5]Jing Hu, Xiaoli Lin, Xiaolong Zhang:
Protein Hot Regions Feature Research Based on Evolutionary Conservation. ICIC (2) 2017: 254-260 - [c4]Xiaoli Lin, Xiaolong Zhang, Jing Hu:
Classification of Hub Protein and Analysis of Hot Regions in Protein-Protein Interactions. ICIC (2) 2017: 365-374 - 2015
- [j1]Jing Hu, Xiaolong Zhang, Xiaoming Liu, Jinshan Tang:
Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification. Comput. Biol. Medicine 61: 127-137 (2015) - [c3]Jing Hu, Xiaolong Zhang:
Prediction of hot regions in protein-protein interaction by density-based incremental clustering with parameter selection. BIBM 2015: 1162-1169 - [c2]Jing Hu, Xiaolong Zhang:
Testing whether hot regions in protein-protein interactions are conserved in different species. BIBM 2015: 1624-1629 - [c1]Jing Hu, Xiaolong Zhang:
Identification of Hot Regions in Protein Interfaces: Combining Density Clustering and Neighbor Residues Improves the Accuracy. ICIC (2) 2015: 399-407
Coauthor Index
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