Both DNA and protein microarrays are prone to systematic errors that are usually generated from different sources, such as surface defects and spatial artifacts. Many studies have offered insight on noise subtraction in DNA microarrays [11] [12] [13] [14] , but little investigation has been done for protein microarrays. Functional protein microarrays differ in many respects from DNA microarrays. First, the goals of these two microarrays are different. DNA microarrays measure the relative DNA levels in a pool of probes, whereas functional protein arrays often aim at discovering global interactions of a single probe molecule. Second, a typical DNA microarray experiment measures signal ratios between two color channels, one for a tested mRNA sample and the other for a reference sample [15] . Signals in the second channel may serve as intrinsic controls that can help to decrease the effects of various amounts of reagent on the arrays and any local array nonuniformity. Furthermore, many current scaling methods are then based on the assumption that signal intensities should be balanced between the two color channels despite variation in slide location, intensity and other sources of systematic variation [16] [17] [18] . However, such controls are missing in onecolor-channel protein microarrays. Third, several scaling approaches in DNA microarrays are based on a set of 'housekeeping' genes that give constant signal intensities at different conditions [19, 20] . However, in protein microarrays, such a control group must be customized according to the type of activities that are assayed, and, therefore, a ubiquitous reference group does not exist. Fourth, unlike DNA microarrays, in which non-specific binding can often be addressed by signal comparison with mismatch probes [21] , cross-reactivities of protein microarrays can not be as directly corrected for. A separate slide is, therefore, often required to be probed in parallel as a negative control in protein microarray experiments. Finally, several protein-specific artifacts serve as common noise sources in protein microarrays. In the kinase assay, for example, the signal from strongly phosphorylated spots can bleed into neighboring spots, leading to incorrect background measurement. These differences are particularly applicable to functional protein microarrays in comparison to antibody arrays, and, therefore, the normalization techniques used for DNA microarrays are usually not directly applicable to functional protein microarrays.