Multivariate analysis of data from two-dimensional electrophoretic separation of macromolecules

Abstract

Recent work on two-dimensional electrophoretic separation of molecules has concentrated on technical aspects of molecule identification, leaving little in the way of time and resources to explore new, effective methods for analyzing the data thus produced. We present a method for coding electrophorograms that is capable of capturing sufficient information in order that subsequent analysis might be revealing. Along with this coding method, we describe a flexible approach to the analysis of electrophoretic data employing multivariate methods for summarization and comparison. In this we have found an effective vehicle for revealing some unexpected properties of the electrophorograms.