Expression databases, including the Gene Expression Omnibus and ArrayExpress, have experienced significant growth over the past decade and now hold hundreds of thousands of arrays from multiple species. Since most drugs are initially tested on model organisms, the ability to compare expression experiments across species may help identify pathways that are activated in a similar way in humans and other organisms. However, while several methods exist for finding co-expressed genes in the same species as a query gene, looking at co-expression of homologs or arbitrary genes in other species is challenging. Unlike sequence, which is static, expression is dynamic and changes between tissues, conditions and time. Thus, to carry out cross-species analysis using these databases, we need methods that can match experiments in one species with experiments in another species.