Background#R##N#Two-Dimensional Difference In Gel Electrophoresis (2D-DIGE) is a powerful tool for measuring differences in protein expression between samples or conditions. However, to remove systematic variability within and between gels the data has to be normalized.#R##N##R##N#In this study we examined the ability of four existing and four novel normalization methods to remove systematic bias in data produced with 2D-DIGE. We also propose a modification of an existing method where the statistical framework determines whether a set of proteins shows an association with the predefined phenotypes of interest. This method was applied to our data generated from a monkey model (Macaca fascicularis) of Parkinson's disease.
['Kim Kultima', 'Birger Scholz', 'Henrik Alm', 'Karl Sköld', 'Marcus Svensson', 'Alan R. Crossman', 'Erwan Bezard', 'Per E. Andrén', 'Ingrid Lönnstedt']
Normalization and expression changes in predefined sets of proteins using 2D gel electrophoresis: A proteomic study of L-DOPA induced dyskinesia in an animal model of Parkinson's disease using DIGE