Multi-class tumor classification by discriminant partial least squares using microarray gene expression data and assessment of classification models
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Publication:2490602
DOI10.1016/j.compbiolchem.2004.05.002zbMath1088.92042OpenAlexW1991680649WikidataQ30945276 ScholiaQ30945276MaRDI QIDQ2490602
Publication date: 16 May 2006
Published in: Computational Biology and Chemistry (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.compbiolchem.2004.05.002
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50)
Related Items (5)
Effective dimensionality reduction using kernel locality preserving partial least squares discriminant analysis ⋮ Hybrid particle swarm optimization and tabu search approach for selecting genes for tumor classification using gene expression data ⋮ Genome-based identification of diagnostic molecular markers for human lung carcinomas by PLS-DA ⋮ Borrowing information from relevant microarray studies for sample classification using weighted partial least squares ⋮ Exploiting scale-free information from expression data for cancer classification
Cites Work
- Significance analysis of microarrays applied to the ionizing radiation response
- Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
- The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses
- Selection bias in gene extraction on the basis of microarray gene-expression data
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