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.
Marengo
Emilio
E
Department of Environmental and Life Sciences, University of Eastern Piedmont, Via Bellini 25/G, 15100 Alessandria, Italy. marengoe@tin.it
Robotti
Elisa
E
Bobba
Marco
M
Righetti
Pier Giorgio
PG
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