Lihong Peng
Orcid: 0000-0002-2321-3901
According to our database1,
Lihong Peng
authored at least 22 papers
between 2004 and 2024.
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Bibliography
2024
CellDialog: A Computational Framework for Ligand-Receptor-Mediated Cell-Cell Communication Analysis.
IEEE J. Biomed. Health Informatics, January, 2024
2023
STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering.
Comput. Biol. Medicine, November, 2023
Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data.
Comput. Biol. Medicine, September, 2023
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., March, 2023
2022
Finding lncRNA-Protein Interactions Based on Deep Learning With Dual-Net Neural Architecture.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
VDA-RWLRLS: An anti-SARS-CoV-2 drug prioritizing framework combining an unbalanced bi-random walk and Laplacian regularized least squares.
Comput. Biol. Medicine, 2022
Cell-cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies.
Briefings Bioinform., 2022
Analyses of cell-to-cell communication combining a heterogeneous deep ensemble framework and scoring approaches from single-cell RNA sequencing data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
A deep learning-based unsupervised learning method for spatially resolved transcriptomic data analysist.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
Identifying possible lncRNA-disease associations based on deep learning and positive-unlabeled learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
LPI-deepGBDT: a multiple-layer deep framework based on gradient boosting decision trees for lncRNA-protein interaction identification.
BMC Bioinform., 2021
LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification.
BMC Bioinform., 2021
LPI-EnEDT: an ensemble framework with extra tree and decision tree classifiers for imbalanced lncRNA-protein interaction data classification.
BioData Min., 2021
Dynamic PET Image Denoising Using Deep Image Prior Combined With Regularization by Denoising.
IEEE Access, 2021
2018
Improved DNA-Binding Protein Identification by Incorporating Evolutionary Information Into the Chou's PseAAC.
IEEE Access, 2018
2017
IEEE J. Biomed. Health Informatics, 2017
2015
IEEE ACM Trans. Comput. Biol. Bioinform., 2015
2014
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
2011
Proceedings of the IEEE 10th International Conference on Trust, 2011
2010
A network comparison algorithm for predicting the conservative interaction regions in protein-protein interaction network.
Proceedings of the Fifth International Conference on Bio-Inspired Computing: Theories and Applications, 2010
2009
Proceedings of the CSIE 2009, 2009 WRI World Congress on Computer Science and Information Engineering, March 31, 2009
2004
An exploration of the uncertainty relation satisfied by BP network learning ability and generalization ability.
Sci. China Ser. F Inf. Sci., 2004