title: Decoding 2-D Maps by Autocovariance Function.
abstract: This chapter describes a mathematical approach based on the study of the 2-D autocovariance function (2-D ACVF) useful for decoding the complex signals resulting from the separation of protein mixtures. The method allows to obtain fundamental analytical information hidden in 2-D PAGE maps by spot overlapping, such as the number of proteins present in the sample and the mean standard deviation of the spots, describing the separation performance. In addition, it is possible to identify ordered patterns potentially present in spot positions, which can be related to the chemical composition of the protein mixture, such as post-translational modifications.The procedure was validated on computer-simulated maps and successfully applied to reference maps obtained from literature sources.
authors.affiliation: Department of Chemical and Pharmaceutical Sciences, University of Ferrara, Via Fossato di Mortara 17/19, 44121, Ferrara, Italy.
authors.forename: Maria Chiara
authors.initials: MC
authors.lastname: Pietrogrande
authors.affiliation: Department of Chemical and Pharmaceutical Sciences, University of Ferrara, Via Fossato di Mortara 17/19, 44121, Ferrara, Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Marchetti
authors.affiliation: Department of Chemical and Pharmaceutical Sciences, University of Ferrara, Via Fossato di Mortara 17/19, 44121, Ferrara, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Dondi
mesh_terms: D003198:Computer Simulation; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods*; D011499:Protein Processing, Post-Translational / Q000235:genetics; D011506:Proteins / Q000737:chemistry* / Q000302:isolation & purification; D040901:Proteomics / Q000379:methods*
chemical_list: D011506:Proteins
keywords: 2-D PAGE (2-D polyacrylamide gel electrophoresis ) maps; Bidimensional autocovariance function; Bioinformatics; Chemometric methods; Spot overlapping