title: ProCAT: a data analysis approach for protein microarrays.
abstract: Protein microarrays provide a versatile method for the analysis of many protein biochemical activities. Existing DNA microarray analytical methods do not translate to protein microarrays due to differences between the technologies. Here we report a new approach, ProCAT, which corrects for background bias and spatial artifacts, identifies significant signals, filters nonspecific spots, and normalizes the resulting signal to protein abundance. ProCAT provides a powerful and flexible new approach for analyzing many types of protein microarrays.
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Zhu
authors.forename: Mark
authors.initials: M
authors.lastname: Gerstein
authors.forename: Michael
authors.initials: M
authors.lastname: Snyder
mesh_terms: D017868:Cyclic AMP-Dependent Protein Kinases / Q000378:metabolism; D040081:Protein Array Analysis / Q000379:methods* / Q000592:standards; D011786:Quality Control; D012372:ROC Curve; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D012984:Software
chemical_list: D017868:Cyclic AMP-Dependent Protein Kinases