Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1180818 | Chemometrics and Intelligent Laboratory Systems | 2006 | 5 Pages |
Abstract
Discriminant partial least squares regression is used for classifying two leukaemia subtypes. Clusters from a hierarchical clustering are tested for significance by jack-knife. Cross model validation is used both to detect the optimal partitioning of genes and to validate the feature selection. A predictive model based on 24 out of 500 initial clusters proved to outperform a model based on single genes for the presented data. Some of the selected clusters were shown to be biologically meaningful, others may give clues to functional relationships.
Keywords
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Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Lars Gidskehaug, Endre Anderssen, Bjørn K. Alsberg,