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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.
SUBMITTER: Monfort-Lanzas P
PROVIDER: S-EPMC9272810 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
Monfort-Lanzas Pablo P Gronauer Raphael R Madersbacher Leonie L Schatz Christoph C Rieder Dietmar D Hackl Hubert H
Bioinformatics (Oxford, England) 20220701 14
<h4>Summary</h4>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 analys ...[more]