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Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints.

J. Wang, C. Lu, J. Liu, L. Dai, and X. Kong. BMC Bioinform., 20-S (22): 718 (2019)

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Seunghyun Kong

Thay Kong

Xiangqing Kong

Wei Xiang

Ming Xiang

Other publications of authors with the same name

Multi-view manifold regularized compact low-rank representation for cancer samples clustering on multi-omics data.J. Wang, C. Lu, X. Kong, L. Dai, S. Yuan, and X. Zhang. BMC Bioinform., 22-S (12): 334 (January 2022)Sparse Orthogonal Nonnegative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Tumor Samples.L. Dai, J. Liu, R. Zhu, X. Kong, M. Hou, and S. Yuan. BIBM, page 1332-1337. IEEE Computer Society, (2018)Joint CC and Bimax: A Biclustering Method for Single-Cell RNA-Seq Data Analysis.H. Chu, X. Kong, J. Liu, J. Wang, S. Yuan, and L. Dai. ISBRA, volume 13064 of Lecture Notes in Computer Science, page 499-510. Springer, (2021)Hyper-graph Robust Non-negative Matrix Factorization Method for Cancer Sample Clustering and Feature Selection.C. Jiao, T. Wu, J. Liu, and X. Kong. IDMB, volume 1099 of Communications in Computer and Information Science, page 112-125. Springer, (2019)Extreme Learning Machine Based on Double Kernel Risk-Sensitive Loss for Cancer Samples Classification.Z. Niu, L. Ren, R. Zhu, X. Kong, Y. Gao, and J. Liu. ICIC (2), volume 12837 of Lecture Notes in Computer Science, page 532-539. Springer, (2021)Network analysis based on low-rank method for mining information on integrated data of multi-cancers.M. Hou, Y. Gao, J. Liu, L. Dai, X. Kong, and J. Shang. Comput. Biol. Chem., (2019)Kernel Risk-Sensitive Loss based Hyper-graph Regularized Robust Extreme Learning Machine and Its Semi-supervised Extension for Classification.L. Ren, J. Liu, Y. Gao, X. Kong, and C. Zheng. Knowl. Based Syst., (2021)Dual Graph-Laplacian PCA: A Closed-Form Solution for Bi-Clustering to Find "Checkerboard" Structures on Gene Expression Data.J. Liu, C. Feng, X. Kong, and Y. Xu. IEEE Access, (2019)Laplacian regularized low-rank representation for cancer samples clustering.J. Wang, J. Liu, X. Kong, S. Yuan, and L. Dai. Comput. Biol. Chem., (2019)Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints.J. Wang, C. Lu, J. Liu, L. Dai, and X. Kong. BMC Bioinform., 20-S (22): 718 (2019)

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Disambiguation of "Kong, Xiang-Zhen"

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Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints.

Please choose a person to relate this publication to

Seunghyun Kong

Thay Kong

Xiangqing Kong

Wei Xiang

Ming Xiang

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Kong, Xiang-Zhen"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints.

Please choose a person to relate this publication to

Seunghyun Kong

Thay Kong

Xiangqing Kong

Wei Xiang

Ming Xiang

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints.