Other articles in the series can be found online at http://ccforum.com/articles/ theme-series.asp?series=CC_Trans ProCAT: a data analysis approach for protein microarrays 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. DNA microarray technologies have proven to be extremely valuable for probing biological processes by measuring mRNA expression profiles. However, studies at the protein level have the potential to provide more direct information since most genes function through their protein products. Traditional investigations focus on individual proteins in a system and then combine such individual analyses to provide a more global perspective. Recently, technologies to analyze proteins in a high throughput and unbiased fashion have become feasible [1] . One particular powerful technology is protein microarrays, which contain a high density of proteins and allow a systematic probing of biochemical activities [2, 3] .