miRAnno-network-based functional microRNA annotation

Tomas Tokar; Chiara Pastrello; Mark Abovsky; Sara Rahmati; Igor Jurisica

doi:10.1093/bioinformatics/btab527

miRAnno-network-based functional microRNA annotation

Bioinformatics. 2022 Jan 3;38(2):592-593. doi: 10.1093/bioinformatics/btab527.

Authors

Tomas Tokar¹, Chiara Pastrello¹, Mark Abovsky¹, Sara Rahmati¹, Igor Jurisica^{1

2

3}

Affiliations

¹ Osteoarthritis Research Program Division of Orthopedic Surgery Schroeder Arthritis Institute, and Data Science Discovery Centre for Chronic Diseases Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.
² Departments of Medical Biophysics and Computer Science, University of Toronto, Toronto, Ontario, Canada.
³ Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia.

PMID: 34297061
DOI: 10.1093/bioinformatics/btab527

Abstract

Motivation: Functional annotation is a common part of microRNA (miRNA)-related research, typically carried as pathway enrichment analysis of the selected miRNA targets. Here, we propose miRAnno, a fast and easy-to-use web application for miRNA annotation.

Results: miRAnno uses comprehensive molecular interaction network and random walks with restart to measure the association between miRNAs and individual pathways. Independent validation shows that miRAnno achieves higher signal-to-noise ratio compared to the standard enrichment analysis.

Availability and implementation: miRAnno is freely available at https://ophid.utoronto.ca/miRAnno/.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

MicroRNAs* / genetics
Software

Substances

MicroRNAs

Abstract

Publication types

MeSH terms

Substances

Grants and funding