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BMCBI
2008
138views more  BMCBI 2008»
13 years 4 months ago
Combining transcriptional datasets using the generalized singular value decomposition
Background: Both microarrays and quantitative real-time PCR are convenient tools for studying the transcriptional levels of genes. The former is preferable for large scale studies...
Andreas W. Schreiber, Neil J. Shirley, Rachel A. B...
EACL
2006
ACL Anthology
13 years 5 months ago
Generalized Hebbian Algorithm for Incremental Singular Value Decomposition in Natural Language Processing
An algorithm based on the Generalized Hebbian Algorithm is described that allows the singular value decomposition of a dataset to be learned based on single observation pairs pres...
Genevieve Gorrell
GPB
2010
231views Solid Modeling» more  GPB 2010»
13 years 1 months ago
Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decompos
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
Ferran Reverter, Esteban Vegas, Pedro Sánch...
BMCBI
2008
145views more  BMCBI 2008»
13 years 4 months ago
Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis
Background: The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, ...
Shameek Biswas, John D. Storey, Joshua M. Akey
GECCO
2005
Springer
186views Optimization» more  GECCO 2005»
13 years 10 months ago
Subproblem optimization by gene correlation with singular value decomposition
Several ways of using singular value decomposition (SVD), a linear algebra technique typically used for information retrieval, to decompose problems into subproblems are investiga...
Jacob G. Martin