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- Two methods for identifying transcription factors for lists of differentially expressed genes (ChEA and PWM)
- Large-scale protein-protein interaction network made from 18 sources with the ability to build subnetworks that connect seed lists of genes/proteins
- Kinase enrichment analysis tool and a database of kinase-substrate interactions
- Gene-list enrichment analysis tool with 14 gene-set libraries
- A tool for identifying drugs that induce or reverse the expression of lists of differentially expressed genes
ABSTRACT: 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. Here we present a new approach called Expression2Kinases (X2K) to identify upstream regulators likely responsible for observed patterns in genome-wide gene expression. By integrating ChIP-seq/chip and position-weight-matrices (PWMs) data, protein-protein interactions, and kinase-substrate phosphorylation reactions we can better 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. The X2K approach can advance our understanding of cell signaling and unravel drugs mechanisms of action.