A scaling method that reduces signal variations among spots of the same proteins at different array locations decreases spatial artifacts. We developed a new normalization method to deal with the spatial artifacts specific to functional protein microarrays. By assuming that signal distribution in large windows is consistent across the slide, the foreground signal of each spot can be normalized according to signal intensities in its surrounding neighborhood. This assumption is usually valid in protein microarray experiments in which proteins are randomly printed on the array ( Figure 3 ). Two parameters, the median and the median absolute deviation (MAD), are calculated to represent the signal distribution in the local window ( Figure 4 ). To perform the normalization, the median and MAD of all sliding windows are averaged. The average values are then used to correct the signal of the central spot to To test the performance of this two-parameter scaling approach for signal normalization within one slide, we designed a test microarray containing multiple positive controls printed at different positions on the slide. The test array was organized in the same format as the commercially available protein microarrays (Invitrogen). Each protein was printed in duplicate, and the array contained 24 blocks of 16 by 16 printed proteins (Figure 5a ). Two GST-fusion proteins, Sla2p and Myo4p, were purified separately and a 1:1, 1:5, and 1:25 dilution of each protein was prepared. Sla2p and Myo4p at each concentration were printed at eight random positions on the array. Other spots were occupied with bovine serum albumin (BSA) as negative controls. In order to visualize the two fusion proteins, anti-GST antibody was used to probe the slide, and one probing with typical spatial artifacts is shown in Figure 5 . The artifact-containing slide showed different signal levels between the edges and the middle portion of the array. This produced blocks that had a variable signal distribution that ranged from high to low from one edge of the slide to the opposite edge; the variability occurred across blocks and simple block normalization methods adopted in DNA microarray normalization approaches [17] would not be suitable for dealing with this problem.