Functionally associated genes tend to be co-expressed, which indicates that they could also be co-regulated. Since co-regulation is usually governed by transcription factors via their specific binding elements, putative regulators can be identified from promoter sets of (co-expressed) genes by screening for over-represented nucleotide patterns. Here, we present a program, POCO, which discovers such over-represented patterns from either one or two promoter sets. Typical microarray experiments yield up- and down-regulated gene sets that may represent, for example, distinct defense pathways. Assuming that a functional transcription factor cannot simultaneously both up- and down-regulate the gene sets, its binding element should respectively be over- and under-represented in the corresponding promoter sets. This idea is implemented in POCO, which tests the hypothesis that the distributions of a pattern differ among three sets of promoters: up-regulated, down-regulated and randomly-chosen. In the program, pattern discovery is based on explicit enumeration of all possible patterns on the alphabet (A, C, G, T and N). The mean occurrences and SDs of the patterns are estimated using bootstrapping and their significance is assessed using ANOVA F-statistics, Tukey's honestly significantly difference test and P-values. The program is freely available at http://ekhidna.biocenter.helsinki.fi/poco.