Acta Chromatographica
Volume/Issue:
Volume 23: Issue 1
The use of chemometrics to analyse protein patterns from gel electrophoresis
Authors:
E. M. Faergestad Nofima Mat AS, Osloveien 1, 1430, Ås, Norway

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,
M. B. Rye NTNU, 7491, Trondheim, Norway

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,
S. Nhek Nofima Mat AS, Osloveien 1, 1430, Ås, Norway

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K. Hollung Nofima Mat AS, Osloveien 1, 1430, Ås, Norway

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H. Grove Cigene, University of Life Science, PO Box 5003, 1430, Ås, Norway

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Pages:
1–40
Online Publication Date:
01 Mar 2011
Publication Date:
01 Mar 2011
Article Category:
Review Article
DOI:
https://doi.org/10.1556/achrom.23.2011.1.1
Keywords:
2DE; gel electrophoresis; bioinformatics; multivariate data analysis; regression; classification; partial least-squares; principal-components analysis; cluster analysis; neural networks
Open access

Summary

Chemometrics involves strategies to analyse multivariate data using interdisciplinary approaches aiming to extract relevant information from complex data. Chemometric strategies comprise both the pre-processing of the data, where the choice of methodology is domain-specific, and analysis of the resulting data after preprocessing using multivariate methodology. Although use of multivariate data analysis for gel electrophoresis images has increased substantially in the last decade, its use is still much less frequent than use of univariate approaches. Considering the complexity of the electrophoresis gel images and the multivariate nature of the proteome, applying multivariate data analysis for gel electrophoresis images gives information which is otherwise lost. This paper is written as a review and guideline of chemometric strategies used for analysis of gel electrophoresis images. The multivariate data analyses described are, however, also relevant for other proteome data, for example mass spectrometry, and for functional genomics in general.

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