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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)

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Tianxiang Dai University of Stuttgart

Anni Dai University of Stuttgart

G. Daiß

Gregor Daiß University of Stuttgart

Other publications of authors with the same name

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. Computational Biology and Chemistry, (2019)Integrative graph regularized matrix factorization for drug-pathway associations analysis.L. Dai, C. Zheng, J. Liu, R. Zhu, S. Yuan, J. Wang, and X. Kong. Computational Biology and Chemistry, (2019)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)Low-rank representation regularized by L2, 1-norm for identifying differentially expressed genes.Y. Wang, J. Liu, Y. Gao, C. Zheng, and L. Dai. BIBM, page 626-629. IEEE Computer Society, (2017)Robust graph regularized discriminative nonnegative matrix factorization for characteristic gene selection.L. Dai, C. Feng, J. Liu, C. Zheng, M. Hou, and J. Yu. BIBM, page 1253-1258. IEEE, (2016)L2, 1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions.Z. Cui, Y. Gao, J. Liu, L. Dai, and S. Yuan. BMC Bioinformatics, 20-S (8): 287:1-287:13 (2019)Laplacian regularized low-rank representation for cancer samples clustering.J. Wang, J. Liu, X. Kong, S. Yuan, and L. Dai. Computational Biology and Chemistry, (2019)A Fast Quantum Clustering Approach for Cancer Gene Clustering.R. Zhu, G. Li, J. Liu, L. Dai, S. Yuan, and Y. Guo. BIBM, page 1610-1613. IEEE Computer Society, (2018)PCA via joint graph Laplacian and sparse constraint: Identification of differentially expressed genes and sample clustering on gene expression data.C. Feng, Y. Xu, M. Hou, L. Dai, and J. Shang. BMC Bioinformatics, 20-S (22): 716 (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 Bioinformatics, 20-S (22): 718 (2019)

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Disambiguation of "Dai, Ling-Yun"

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Sparse Orthogonal Nonnegative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Tumor Samples.

Please choose a person to relate this publication to

Tianxiang Dai University of Stuttgart

Anni Dai University of Stuttgart

G. Daiß

Gregor Daiß University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Dai, Ling-Yun"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Sparse Orthogonal Nonnegative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Tumor Samples.

Please choose a person to relate this publication to

Tianxiang Dai University of Stuttgart

Anni Dai University of Stuttgart

G. Daiß

Gregor Daiß University of Stuttgart

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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Chicago
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Sparse Orthogonal Nonnegative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Tumor Samples.