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Article Abstract

Summary: MicroRNAs have been shown to be able to modulate the tumor microenvironment and the immune response and hence could be interesting biomarkers and therapeutic targets in immuno-oncology; however, dedicated analysis tools are missing. Here, we present a user-friendly web platform MIO and a Python toolkit miopy integrating various methods for visualization and analysis of provided or custom bulk microRNA and gene expression data. We include regularized regression and survival analysis and provide information of 40 microRNA target prediction tools as well as a collection of curated immune related gene and microRNA signatures and processed TCGA data including estimations of infiltrated immune cells and the immunophenoscore. The integration of several machine learning methods enables the selection of prognostic and predictive microRNAs and gene interaction network biomarkers.

Availability And Implementation: https://mio.icbi.at, https://github.com/icbi-lab/mio and https://github.com/icbi-lab/miopy.

Supplementary Information: Supplementary data are available at Bioinformatics online.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9272810PMC
http://dx.doi.org/10.1093/bioinformatics/btac366DOI Listing

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