title: Multiple Testing and Pattern Recognition in 2-DE Proteomics.
abstract: After separation through two-dimensional gel electrophoresis (2-DE), several hundreds of individual protein abundances can be quantified in a cell population or sample tissue. However, gel-based proteomics has the reputation of being a slow and cumbersome art. But art is not dead! While 2-DE may no longer be the tool of choice in high-throughput differential proteomics, it is still very effective to identify and quantify protein species caused by genetic variations, alternative splicing, and/or PTMs. This chapter reviews some typical statistical exploratory and confirmatory tools available and suggests case-specific guidelines for (1) the discovery of potentially interesting protein spots, and (2) the further characterization of protein families and their possible PTMs.
authors.affiliation: Department of Biosystems, Faculty of Bioscience Engineering, K.U. Leuven, Willem Decroylaan 42, Leuven, 3001, Belgium. sebastien.carpentier@biw.kuleuven.be.|SYBIOMA: Facility for Systems Biology Based Mass Spectrometry, Herestraat 49 O&N2, Leuven, 3000, Belgium. sebastien.carpentier@biw.kuleuven.be.
authors.forename: Sebastien C
authors.initials: SC
authors.lastname: Carpentier
mesh_terms: D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods* / Q000706:statistics & numerical data; D057166:High-Throughput Screening Assays; D007091:Image Processing, Computer-Assisted; D013058:Mass Spectrometry / Q000379:methods; D011506:Proteins / Q000737:chemistry / Q000302:isolation & purification*; D040901:Proteomics / Q000706:statistics & numerical data*
chemical_list: D011506:Proteins
keywords: 2-DE; Clustering; Multivariate statistics; Protein correlations; Protein isoforms