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Treffer: Targeted projection pursuit for visualizing gene expression data classifications

Title:
Targeted projection pursuit for visualizing gene expression data classifications
Source:
Bioinformatics (Oxford. Print). 22(21):2667-2673
Publisher Information:
Oxford: Oxford University Press, 2006.
Publication Year:
2006
Physical Description:
print, 15 ref
Original Material:
INIST-CNRS
LGMI
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Northumbria University, Newcastle, United Kingdom
Bournemouth University, Bournemouth, United Kingdom
ISSN:
1367-4803
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Biological sciences. Generalities. Modelling. Methods

Generalities in biological sciences
Accession Number:
edscal.18282004
Database:
PASCAL Archive

Weitere Informationen

We present a novel method for finding low-dimensional views of high-dimensional data: Targeted Projection Pursuit. The method proceeds by finding projections of the data that best approximate a target view. Two versions of the method are introduced; one version based on Procrustes analysis and one based on an artificial neural network. These versions are capable of finding orthogonal or non-orthogonal projections, respectively. The method is quantitatively and qualitatively compared with other dimension reduction techniques. It is shown to find 2D views that display the classification of cancers from gene expression data with a visual separation equal to, or better than, existing dimension reduction techniques.