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Integrative graph regularized matrix factorization for drug-pathway associations analysis.

, , , , , , and . Computational Biology and Chemistry, (2019)

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Integrative graph regularized matrix factorization for drug-pathway associations analysis., , , , , , and . Computational Biology and Chemistry, (2019)Network analysis based on low-rank method for mining information on integrated data of multi-cancers., , , , , and . Computational Biology and Chemistry, (2019)Sparse Orthogonal Nonnegative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Tumor Samples., , , , , and . BIBM, page 1332-1337. IEEE Computer Society, (2018)Low-rank representation regularized by L2, 1-norm for identifying differentially expressed genes., , , , and . BIBM, page 626-629. IEEE Computer Society, (2017)Robust graph regularized discriminative nonnegative matrix factorization for characteristic gene selection., , , , , and . BIBM, page 1253-1258. IEEE, (2016)Laplacian regularized low-rank representation for cancer samples clustering., , , , and . Computational Biology and Chemistry, (2019)L2, 1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions., , , , and . BMC Bioinformatics, 20-S (8): 287:1-287:13 (2019)A Fast Quantum Clustering Approach for Cancer Gene Clustering., , , , , and . 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., , , , and . BMC Bioinformatics, 20-S (22): 716 (2019)Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints., , , , and . BMC Bioinformatics, 20-S (22): 718 (2019)