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For each miRNA , transcriptional correlations with predicted targets are calculated

Identification of miRNA apt and assessment of influenced genes sets/pathways/signatures. b). a). List of miRNA candidate targets are identified using different prediction algorithms ( miRanda , PicTar , TargetScan , mirBase , miRTarget2, TarBase ). 1. 43 miRNA apt

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For each miRNA , transcriptional correlations with predicted targets are calculated

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  1. Identification of miRNAaptand assessment of influenced genes sets/pathways/signatures b) a) List of miRNA candidate targets are identified using different prediction algorithms (miRanda, PicTar, TargetScan, mirBase, miRTarget2, TarBase) 1. 43miRNAapt (Fisher test FDR < 0.05) Enrichment for anti-correlated predicted targets -log10 FDR For each miRNA, transcriptional correlations with predicted targets are calculated 2. FDR = 0.05 miRNAs Checks that predicted targets are enriched for anti-correlated genes (Fisher-test based q-value < 0.05). If so, the miRNA is labelled as a miRNAapt 3. signature gene set (e.g. “FGF SIGNALING”) genes resulting as candidate targets and anti-correlated to the miRNAap For each miRNAaptlists of anti-correlated candidate targets (assumed to be “bona fide” miRNAapttargets) are screened for gene set enrichment using a large compendium of gene sets representing pathways and transcriptional signatures 4. statistical significance of the overlap (FDR on Fisher test)

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