Analysis of Dynamic Protein Expression Data

Abstract

Difference gel electrophoresis (DIGE) is the new gold standard analysing complex protein mixtures in proteomics. It is used for measuring the expression levels of proteins in different mixtures on the same two-dimensional electrophoresis (2-DE) gel. In this paper we review a method for the calibration and normalization of those protein expression measurements. Further we show how to find treatment effects and time-treatment-interactions in longitudinal data obtained from DIGE experiments. A problem in those data sets is the existence of a lot of missing values. Therefore, we propose a method for the estimation of missing data points.

Keywords

• difference gel electrophoresis
• data calibration
• mixed linear model for longitudinal data
• missing values
• proteomics