The X2K Appyter (Expression2Kinases) predicts upstream regulatory networks associated with user-inputted sets of genes. Discrete query gene sets are compared first to ChEA3 libraries of transcription factor target gene sets assembled from orthogonal 'omics' datasets. Afterwards, ChEA3 results are put through a protein-protein interaction database to determine the transcription factor intermediate protein interactors. Finally, protein interactors are compared to the KEA3 background database—which contains measured and predicted kinase-substrate interactions, kinase-protein interactions, and interactions supported by co-expression and co-occurrence data—to determine which kinases may be most closely associated with the transcription factor intermediate protein interactors. Overall, Expression2Kinases can provide a method of identifying upstream regulators likely responsible for observed patterns in genome-wide gene expression.
