eigengene (Q113330977)
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one of a set of right singular vectors of a genes x samples matrix that tabulates, e.g., the mRNA or gene expression of the genes across the samples
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English | eigengene |
one of a set of right singular vectors of a genes x samples matrix that tabulates, e.g., the mRNA or gene expression of the genes across the samples |
Statements
1 reference
September 2015
inventor of the "eigengene," she pioneered the matrix and tensor modeling of large-scale molecular biological data, which, as she demonstrated, can be used to correctly predict previously unknown cellular mechanisms. (English)
Eigengenes following Alter et al. PNAS 2000 and Alter and Golub PNAS 2006.png
7,642 × 6,061; 3.58 MB
7,642 × 6,061; 3.58 MB
Eigengenes computed by the SVD of a genes x samples matrix that tabulates, e.g., the mRNA expression of the genes across the samples. (English)
4 references
1999, Orly Alter et al., ‘‘Singular Value Decomposition for Gene Expression Data Processing and Modeling.’’ In: After the Genome V (December 6–10, 1999, Jackson Hole, WY) (English)
2 references
September 2015
Dr. Orly Alter
Dr. Orly Alter is a USTAR associate professor of bioengineering and human genetics at the Scientific Computing and Imaging Institute and the Huntsman Cancer Institute at the University of Utah. Inventor of the "eigengene," she pioneered the matrix and tensor modeling of large-scale molecular biological data, which, as she demonstrated, can be used to correctly predict previously unknown cellular mechanisms. (English)
1990s
2 references
1999, Orly Alter et al., ‘‘Singular Value Decomposition for Gene Expression Data Processing and Modeling.’’ In: After the Genome V (December 6–10, 1999, Jackson Hole, WY) (English)
We describe the use of singular value decomposition in transforming gene expression data from genes/arrays space to ‘‘eigengenes’’/‘‘eigenarrays’’ space, where the eigengenes and eigenarrays are unique orthonormal superpositions of the genes and arrays, respectively. (English)
Alter Lab (English)
We describe the use of singular value decomposition in transforming gene expression data from genes/arrays space to ‘‘eigengenes’’/‘‘eigenarrays’’ space, where the eigengenes and eigenarrays are unique orthonormal superpositions of the genes and arrays, respectively. (English)
October 1999
September 2000
January 2001
April 2002
October 2003
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January 2004
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November 2004
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November 2005
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August 2006
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October 2006
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