Genome-wide mRNA profiling provides a snapshot of the global state of cells under different conditions. However, mRNA levels do not provide direct understanding of upstream regulatory mechanisms. Expression2Kinases (X2K) is a new approach to identify upstream regulators likely responsible for observed changes in genome-wide gene expression. By integrating ChIP-seq/chip and position-weight-matrices (PWMs) data, protein-protein interactions, and kinase-substrate phosphorylation reactions X2K can be used to identify regulatory mechanisms upstream of genome-wide differences in gene expression. The idea is to first infer the most likely transcription factors that regulate the differences in gene expression, then use protein-protein interactions to connect the identified transcription factors using additional proteins for building transcriptional regulatory subnetworks centered on these factors, and finally use kinase-substrate protein phosphorylation reactions, to identify and rank candidate protein-kinases that most likely regulate the formation of the identified transcriptional complexes. X2K also contains tools to perform gene-list enrichment analyses and predict drugs that can reverse or aggravate changes in gene expression. The X2K approach can advance our understanding of cell signaling and unravel drugs mechanisms of action.
Requirements:
Java Runtime Environment 6.0
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