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Deterministic projection by growing cell structure networks for visualization of high-dimensionality datasets.

Abstract:

Recent advances in clinical proteomics data acquisition have led to the generation of datasets of high complexity and dimensionality. We present here a visualization method for high-dimensionality datasets that makes use of neuronal vectors of a trained growing cell structure (GCS) network for the projection of data points onto two dimensions. The use of a GCS network enables the generation of the projection matrix deterministically rather than randomly as in random projection. Three datasets...

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Publication status:
Published

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Publisher copy:
10.1016/j.jbi.2005.02.002

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Sub department:
Physical & Theoretical Chem
Role:
Author
Journal:
Journal of biomedical informatics More from this journal
Volume:
38
Issue:
4
Pages:
322-330
Publication date:
2005-08-01
DOI:
EISSN:
1532-0480
ISSN:
1532-0464
Language:
English
Keywords:
Pubs id:
pubs:33190
UUID:
uuid:f1dcb6ec-5f76-4c26-8933-dcbf46401ca7
Local pid:
pubs:33190
Source identifiers:
33190
Deposit date:
2012-12-19

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