Xiang Chen

Orcid: 0000-0002-4797-8837

Affiliations:
  • Hunan University of Science and Technology, Xiangtan, Hunan, China


According to our database1, Xiang Chen authored at least 12 papers between 2011 and 2024.

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Bibliography

2024
spGCLF: a versatile deep graph contrastive learning framework for spatial transcriptomics analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023
scIAMC:Single-Cell Imputation via adaptive matrix completion.
Proceedings of the 10th IEEE International Conference on Cyber Security and Cloud Computing, 2023

ESR: Optimizing Gene Feature Selection for scRNA-seq Data.
Proceedings of the 10th IEEE International Conference on Cyber Security and Cloud Computing, 2023

A deep graph convolution network with attention for clustering scRNA-seq data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
RNMFLP: Predicting circRNA-disease associations based on robust nonnegative matrix factorization and label propagation.
Briefings Bioinform., 2022

DAESTB: inferring associations of small molecule-miRNA via a scalable tree boosting model based on deep autoencoder.
Briefings Bioinform., 2022

2021
An Ensemble Method to Reconstruct Gene Regulatory Networks Based on Multivariate Adaptive Regression Splines.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

2020
miRTMC: A miRNA Target Prediction Method Based on Matrix Completion Algorithm.
IEEE J. Biomed. Health Informatics, 2020

2019
BiXGBoost: a scalable, flexible boosting-based method for reconstructing gene regulatory networks.
Bioinform., 2019

DoRC: Discovery of rare cells from ultra-large scRNA-seq data.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
PBMarsNet: A Multivariate Adaptive Regression Splines Based Method to Reconstruct Gene Regulatory Networks.
Proceedings of the Bioinformatics Research and Applications - 14th International Symposium, 2018

2011
A local average connectivity-based method for identifying essential proteins from the network level.
Comput. Biol. Chem., 2011


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