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2020 – today
- 2024
[j18]Junyi Peng, Lihong Peng, Zidong Zhou
, Xu Han, Hui Xu, Lijun Lu, Wenbing Lv:
Multi-Level fusion graph neural network: Application to PET and CT imaging for risk stratification of head and neck cancer. Biomed. Signal Process. Control. 92: 106137 (2024)- [j17]Lihong Peng, Pengfei Gao, Wei Xiong, Zejun Li, Xing Chen:
Identifying potential ligand-receptor interactions based on gradient boosted neural network and interpretable boosting machine for intercellular communication analysis. Comput. Biol. Medicine 171: 108110 (2024) - [j16]Lihong Peng, Xin Liu, Min Chen, Wen Liao, Jiale Mao, Liqian Zhou:
MGNDTI: A Drug-Target Interaction Prediction Framework Based on Multimodal Representation Learning and the Gating Mechanism. J. Chem. Inf. Model. 64(16): 6684-6698 (2024) - [j15]Lihong Peng, Wei Xiong, Chendi Han, Zejun Li, Xing Chen:
CellDialog: A Computational Framework for Ligand-Receptor-Mediated Cell-Cell Communication Analysis. IEEE J. Biomed. Health Informatics 28(1): 580-591 (2024) - 2023
- [j14]Lihong Peng, Jingwei Tan, Wei Xiong, Li Zhang, Zhao Wang, Ruya Yuan, Zejun Li, Xing Chen:
Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data. Comput. Biol. Medicine 163: 107137 (2023) - [j13]Lihong Peng, Xianzhi He, Xinhuai Peng, Zejun Li, Li Zhang:
STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering. Comput. Biol. Medicine 166: 107440 (2023) - [j12]Wenbing Lv, Zidong Zhou, Junyi Peng, Lihong Peng, Guoyu Lin, Huiqin Wu, Hui Xu, Lijun Lu:
Functional-structural sub-region graph convolutional network (FSGCN): Application to the prognosis of head and neck cancer with PET/CT imaging. Comput. Methods Programs Biomed. 230: 107341 (2023) - 2022
- [j11]Lihong Peng, Feixiang Wang, Zhao Wang, Jingwei Tan, Li Huang, Xiongfei Tian, Guangyi Liu, Liqian Zhou:
Cell-cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies. Briefings Bioinform. 23(4) (2022) - [j10]Ling Shen, Fuxing Liu, Li Huang, Guangyi Liu, Liqian Zhou, Lihong Peng:
VDA-RWLRLS: An anti-SARS-CoV-2 drug prioritizing framework combining an unbalanced bi-random walk and Laplacian regularized least squares. Comput. Biol. Medicine 140: 105119 (2022) - [j9]Lihong Peng, Chang Wang, Xiongfei Tian, Liqian Zhou, Keqin Li:
Finding lncRNA-Protein Interactions Based on Deep Learning With Dual-Net Neural Architecture. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3456-3468 (2022) - [c7]Lihong Peng, Liangliang Huang, Yuankang Lu, Guangyi Liu, Min Chen, Guosheng Han:
Identifying possible lncRNA-disease associations based on deep learning and positive-unlabeled learning. BIBM 2022: 168-173 - [c6]Lihong Peng, Xianzhi He, Li Zhang, Xinhuai Peng, Yuankang Lu, Zejun Li, Xing Chen:
A deep learning-based unsupervised learning method for spatially resolved transcriptomic data analysist. BIBM 2022: 281-286 - [c5]Lihong Peng, Ruya Yuan, Chendi Han, Jingwei Tan, Zhao Wang, Min Chen, Xing Chen:
Analyses of cell-to-cell communication combining a heterogeneous deep ensemble framework and scoring approaches from single-cell RNA sequencing data. BIBM 2022: 515-522 - 2021
- [j8]Hao Sun, Lihong Peng, Hongyan Zhang, Yuru He, Shuangliang Cao, Lijun Lu:
Dynamic PET Image Denoising Using Deep Image Prior Combined With Regularization by Denoising. IEEE Access 9: 52378-52392 (2021) - [j7]Lihong Peng, Ruya Yuan, Ling Shen, Pengfei Gao, Liqian Zhou:
LPI-EnEDT: an ensemble framework with extra tree and decision tree classifiers for imbalanced lncRNA-protein interaction data classification. BioData Min. 14(1) (2021) - [j6]Liqian Zhou, Zhao Wang, Xiongfei Tian, Lihong Peng:
LPI-deepGBDT: a multiple-layer deep framework based on gradient boosting decision trees for lncRNA-protein interaction identification. BMC Bioinform. 22(1): 479 (2021) - [j5]Liqian Zhou, Qi Duan, Xiongfei Tian, He Xu, Jianxin Tang, Lihong Peng:
LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification. BMC Bioinform. 22(1): 568 (2021)
2010 – 2019
- 2018
- [j4]Xiangzheng Fu, Wen Zhu, Bo Liao, Lijun Cai, Lihong Peng, Jialiang Yang:
Improved DNA-Binding Protein Identification by Incorporating Evolutionary Information Into the Chou's PseAAC. IEEE Access 6: 66545-66556 (2018) - 2017
- [j3]Lihong Peng, Bo Liao, Wen Zhu, Zejun Li, Keqin Li:
Predicting Drug-Target Interactions With Multi-Information Fusion. IEEE J. Biomed. Health Informatics 21(2): 561-572 (2017) - 2015
- [j2]Bo Liao, Yan Jiang, Wei Liang, Lihong Peng, Li Peng, Damien Hanyurwimfura, Zejun Li, Min Chen:
On Efficient Feature Ranking Methods for High-Throughput Data Analysis. IEEE ACM Trans. Comput. Biol. Bioinform. 12(6): 1374-1384 (2015) - 2014
- [c4]Ziheng Jiang, Ping Guo, Lihong Peng:
Locality-Constrained Low-Rank Coding for Image Classification. AAAI 2014: 2780-2786 - 2011
- [c3]Kefei Wang, Heying Zhang, Lihong Peng, Baohua Fan:
Improving the Adaptiveness of FAST TCP Based on the Stability with Time-Delay. TrustCom 2011: 1444-1451 - 2010
- [c2]Lihong Peng, Lipeng Liu, Shi Chen, Quanwei Sheng:
A network comparison algorithm for predicting the conservative interaction regions in protein-protein interaction network. BIC-TA 2010: 34-39
2000 – 2009
- 2009
- [c1]Heying Zhang, Lihong Peng, Baohua Fan, Jie Jiang, Ying Zhang:
Stability of FAST TCP in Single-Link Multi-source Network. CSIE (1) 2009: 369-373 - 2004
- [j1]Zuoyong Li, Lihong Peng:
An exploration of the uncertainty relation satisfied by BP network learning ability and generalization ability. Sci. China Ser. F Inf. Sci. 47(2): 137-150 (2004)
Coauthor Index
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