AbstractCharting miRNA regulation across multiple pathways is central to characterizing their role in disease. Yet, current methods expose only isolated miRNA-pathway interactions. We have developed a systems biology approach, Pathway networks of miRNA Regulation (PanomiR) that identifies miRNAs that coordinately target groups of pathways. PanomiR captures activity dynamics of pathways, detects dysregulated pathways, groups pathways by their co-expression, and detects miRNAs that specifically

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... rget these coordinated groups of dysregulated pathways. We have used PanomiR to explore disease-associated miRNAs and pathways in liver cancer. We show that it recapitulates known and novel liver cancer pathways, determines their up or down regulation, and sensitively captures biologically meaningful signals independent of detectable differential gene expression. PanomiR organizes liver cancer pathways into three broad groups that reflect pathogenic mechanisms of cancer: activation of transcription, cell cycle and proliferation, and dysregulated signalling. Using either experimentally-supported or predicted miRNA-mRNA interactions, PanomiR robustly detects and identifies miRNAs central to liver cancer, unbiased by the number of their gene targets-making it possible to place these cancer miRNAs using PanomiR into the context of co-activated pathways that they regulate. PanomiR is a sensitive, unbiased framework for detection of disease-specific multi-pathway programs under miRNA regulation. PanomiR is accessible as an open-source R/Bioconductor package: <https://bioconductor.org/packages/PanomiR>.