Singular value decomposition for genome-wide expression data processing and modeling (Q29618495)

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Singular value decomposition for genome-wide expression data processing and modeling
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    Singular value decomposition for genome-wide expression data processing and modeling (English)
    3 references
    We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). (English)
    National Research Council, Mathematics and 21st Century Biology. Washington, DC: National Academies Press (July 2005), 149 pp. (English)
    9th most cited Proceedings of the National Academy of Sciences (PNAS) USA paper of the year 2000 and 56th most cited PNAS paper of all time. (English)
    26 August 2022

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