Evaluation of the variables characterized by significant discriminating power in the application of SIMCA classification method to proteomic studies.
SIMCA classification can be applied to 2D-PAGE maps to identify changes occurring in cellular protein contents as a consequence of illnesses or therapies. These data sets are complex to treat due to the large number of proteins detected. A method for identifying relevant proteins from SIMCA discriminating powers is proposed, based on the Box-Cox transformation coupled to probability papers. The method successfully allowed the identification of the relevant spots from 2D maps.
Department of Environmental and Life Sciences, University of Eastern Piedmont, Via Bellini 25/G, 15100 Alessandria, Italy. marengoe@tin.it
Emilio
E
Marengo
Elisa
E
Robotti
Marco
M
Bobba
Pier Giorgio
PG
Righetti
D000818:Animals; D000970:Antineoplastic Agents / Q000627:therapeutic use; D045744:Cell Line, Tumor; D015180:Electrophoresis, Gel, Two-Dimensional; D004727:Endothelium / Q000737:chemistry; D006801:Humans; D006877:Hydroxamic Acids / Q000494:pharmacology; D051379:Mice; D009369:Neoplasms / Q000737:chemistry* / Q000188:drug therapy; D009447:Neuroblastoma / Q000737:chemistry; D010179:Pancreas / Q000737:chemistry; D010190:Pancreatic Neoplasms / Q000737:chemistry; D011336:Probability; D011506:Proteins / Q000032:analysis / Q000145:classification*; D040901:Proteomics; D020123:Sirolimus / Q000627:therapeutic use; D016008:Statistical Distributions; D014747:Vinblastine / Q000627:therapeutic use
D000970:Antineoplastic Agents; D006877:Hydroxamic Acids; D011506:Proteins; C012589:trichostatin A; D014747:Vinblastine; D020123:Sirolimus