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- W2017336508 abstract "The clustering analysis of the cancer gene expression data can provide bases for the early diagnosis of cancer and accurate classification of the cancer subtypes. For the characteristics of cancer gene expression data, an algorithm named FNMF-ITWC (Fast Nonnegative Matrix Factorization Interrelated Two_Way Clustering) is proposed. FNMF-ITWC algorithm firstly selects genes from the original gene expression data, implements non-negative matrix factorization on the row (gene dimension), and then performs clustering on the column (sample dimension). Matlab experimental results show that FNMF-ITWC algorithm improves the computing speed of the algorithm and reduces the data storage space. At the same time, it is able to reveal correlation among genes under certain experimental conditions and the correlation among experiments for some genes." @default.
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- W2017336508 date "2014-10-01" @default.
- W2017336508 modified "2023-09-25" @default.
- W2017336508 title "FNMF-ITWC Algorithm Applied to the Cancer Gene Expression Data" @default.
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- W2017336508 doi "https://doi.org/10.4028/www.scientific.net/amm.678.12" @default.
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