title: 2D-PAGE maps analysis.
abstract: Due to the low reproducibility affecting 2D gel-electrophoresis and the complex maps provided by this technique, the use of effective and robust methods for the comparison and classification of 2D maps is a fundamental tool for the development of automated diagnostic methods. A review of classical and recently developed methods for the comparison of 2D maps is presented here. The methods proposed regard both the analysis of spot volume datasets through multivariate statistical tools (pattern recognition methods, cluster analysis, and classification methods) and the analysis of 2D map images through fuzzy logic, three-way PCA, and the use of moment functions. The theoretical basis of each procedure is briefly introduced, together with a review of the most interesting applications present in recent literature.
authors.affiliation: Department of Environmental and Life Sciences, University of Eastern Piedmont, Alessandria, Italy.
authors.forename: Emilio
authors.initials: E
authors.lastname: Marengo
authors.forename: Elisa
authors.initials: E
authors.lastname: Robotti
authors.forename: Marco
authors.initials: M
authors.lastname: Bobba
mesh_terms: D016000:Cluster Analysis; D030562:Databases, Protein; D016002:Discriminant Analysis; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods* / Q000706:statistics & numerical data; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D010363:Pattern Recognition, Automated; D025341:Principal Component Analysis; D020543:Proteome / Q000145:classification / Q000302:isolation & purification*; D040901:Proteomics / Q000379:methods* / Q000706:statistics & numerical data; D012044:Regression Analysis; D012984:Software
chemical_list: D020543:Proteome