In this extension to the project analyzing top genes via differential expression and fold change values using GSE271486 gene expression data from an NCBI study and reviewing the top genes in the PubMed article free to download based on this data or the outcome article of the data as that study was also an extension to their own study on EBV. We confirmed the 13 genes from the study were 100% accurate in predicting class in a 2 class sample of EBVaNPC or NPC based on study details in this document with links to article and gene expression data. We then add those 13 genes plus the 20 genes we found from top 10 up regulated and top 10 down regulated genes using fold change values and filtering for those sample means not having a 0 value for the gene. We are now moving on to other EBV pathologies from Burkitt and Hodgkin lymphomas that are said to be associated with EBV infection. Also, some other leads to pathologies with EBV associations. We know the association to EBV with multiple sclerosis and Hodgkin's disease is not strong, but we might show it is after we get our database of pathologies and see what the machine predicts in class for these pathologies.

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