Despite these problems, many species detection arrays have been developed [1] [2] [3] [4] [5] . However, reliable methods of data analysis have been rare. Initial methods included visual inspection of the array [4] and clustering [18] , both of which are subjective and time-consuming. To combat this, Urisman et al. [9] have proposed a more robust method, E-Predict. E-Predict utilizes a pre-calculated energy matrix for each oligo on the array and uses a variety of normalization and similarity metrics to calculate a p value and similarity for each virus. The advantages of E-Predict are that it is quantitative, produces good results and is extensible, through the extension of the energy matrix. The disadvantages of the software are a lack of visualization tools, the need to customize parameters for different array platforms and hybridization conditions, and the availability of the software only as a CGI script on the Unix/Linux platform.