AGI uses the gene expression data (depicted as a red/green pseudocolor chart) to select candidate targets for creation of novel antibodies. Microarray technology developed by our collaborators at Stanford University enabled gene expression studies in which over 40,000 genes are examined to identify which gene targets can be used to classify cancer. AGI has used this data to target the production of antibodies specifically focusing on discovering novel markers for classifying solid tissue tumors. Candidate antisera are stained on tumor tissue using tissue arrays to assess their usefulness for immunohistochemistry and tumor classification. Sets of antisera termed 'Panels of Diversity' are tailored to tumors of different tissue origins. Results from antibody staining screens are stored in a custom database. Staining of multiple patient cohorts available as stored paraffin blocks has a created datasets of protein expression across thousands of patient samples and hundred of antibody reagents (depicted as blue/yellow chart pseudocolor chart) revealing a novel approach to tumor classification. By using tissue microarrays, voice recognition scoring software, and an image capturing microscope, AGI has created a database with over one million scored tumors and associated images with over 450GB of useful information.