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Xinhuai Peng

Showing results (1-10 of 4) with videos related to

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Frontiers in Genetics|March 18, 2024
Finding potential lncRNA-disease associations using a boosting-based ensemble learning modelLiqian Zhou, Xinhuai Peng, Lijun Zeng, et al.
Computers in Biology and Medicine|September 22, 2023
STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clusteringLihong Peng, Xianzhi He, Xinhuai Peng, et al.
Gigascience|January 13, 2025
Unveiling patterns in spatial transcriptomics data: a novel approach utilizing graph attention autoencoder and multiscale deep subspace clustering networkLiqian Zhou, Xinhuai Peng, Min Chen, et al.
Interdisciplinary Sciences, Computational Life Sciences|April 1, 2026
KGLAR: Deconvoluting Spatial Transcriptomics Data with Single-cell Transcriptomes through Knowledge-guided NMF and Least Angle RegressionLihong Peng, Feixiang Wang, Wei Wu, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
Frontiers in Genetics|March 18, 2024
Finding potential lncRNA-disease associations using a boosting-based ensemble learning modelLiqian Zhou, Xinhuai Peng, Lijun Zeng, et al.
Computers in Biology and Medicine|September 22, 2023
STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clusteringLihong Peng, Xianzhi He, Xinhuai Peng, et al.
Gigascience|January 13, 2025
Unveiling patterns in spatial transcriptomics data: a novel approach utilizing graph attention autoencoder and multiscale deep subspace clustering networkLiqian Zhou, Xinhuai Peng, Min Chen, et al.
Interdisciplinary Sciences, Computational Life Sciences|April 1, 2026
KGLAR: Deconvoluting Spatial Transcriptomics Data with Single-cell Transcriptomes through Knowledge-guided NMF and Least Angle RegressionLihong Peng, Feixiang Wang, Wei Wu, et al.
Pageof 1