Browse predicted upstream regulatory cell signaling networks inferred from the up- and down-gene expression signatures from 142 human diseases determined by the Expression2Kinases (X2K) algorithm. A list of disease Gene Expression Omnibus (GEO) accession numbers was provided by the Dudley lab and disease gene expression signatures were processed using the Characteristic Direction algorithm. Kinase inhibitors from KINOMEscan were processed the the data collected by the Sorger Lab for the LINCS project.
X2K predicts up-stream transcription factors using ChEA, an enrichment analysis tool developed by the Ma'ayan lab. ChEA uses a background database of transcription factors and their associated target genes extracted from ChIP-seq studies. The Fisher Exact test is used to determine the enriched transcription factors for a given list of differentially expressed genes. X2K then constructs a protein-protein interaction network around the top ten significantly (corrected p-value of < 0.05) enriched transcription factors using Genes2Networks (G2N) which uses known protein-protein interactions collected from 20 online databases describing known protein interactions extracted from the literature. Next, X2K predicts upstream kinases using Kinase Enrichment Analyis (KEA), a kinase enrichment analysis tool that uses a background database of kinase-substrate interactions. KEA uses the Fisher Exact test to determine the significantly enriched kinases for a list of proteins. Finally, enrichment is computed for the kinase inhibitors that target the predicted kinases using the KINOMEscan data collected at HMS by the Sorger Lab. The top five predicted compounds are shown in a bar graph. The compounds' weights are scaled by their enrichment to inhibit the kinases. The predicted up-stream transcription factors, interacting proteins, kinases, and kinase-inhibitors from each disease gene expression signature are shown as interactive networks and bar graphs.
Citation: Chen EY, Xu H, Gordonov S, Lim MP, Perkins MH, Ma'ayan A. Expression2Kinases: mRNA Profiling Linked to Multiple Upstream Regulatory Layers. Bioinformatics. (2012) 28 (1): 105-111 PubMed
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