Abstract: Displays of genetic and/or proteomic expression data can be visually correlated by a user analyzing such expression data. Generally, the user identifies expression data, such as a cluster, a gene, or a protein for example, using conventional user interface techniques. Once expression data are identified by the user, corresponding expression data is identified in other displays. Such corresponding expression data is determined by reference to expression metadata. For each of the other displays of expression data, the corresponding expression data of the other displays is determined according to the expression metadata of those other displays. Within each of those other displays, the corresponding expression data is highlighted within the display to identify the corresponding expression data to the user.

Abstract: Results of statistical clustering and/or correlation analysis of genetic or proteomic expression data such as microarrays, gene chips, or protein chips are used, e.g., as response variables, in further analysis of expression data. In particular, an array of expression data is clustered using a cluster tool to produce an array of expression clusters. Each of the expression clusters represents the same experiments represented by the original expression array. Accordingly, each cluster of the array is of the proper form to be used as a response variable of expression values. Using an expression cluster as a response variable for either supervising clustering or correlation analysis allows correlation between such an expression cluster and other expression data.