miRViz: a novel webserver application to visualize and interpret microRNA datasets

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• MicroRNAs (miRNAs) are crucial regulators of gene expression in eukaryotic cells.
• High-throughput screening generates extensive miRNA datasets that are challenging to interpret.
• Identifying specific miRNAs for further research from large datasets is a common challenge.

Purpose of the Study:

• To present miRViz, a webserver application for visualizing and interpreting large miRNA datasets.
• To enable biologists to generate data-driven hypotheses from miRNA screening results.
• To facilitate straightforward sharing of miRNA datasets with high-quality data representation.

Main Methods:

• Development of a user-friendly webserver application, miRViz, requiring no programming skills.
• Integration of visualization tools for large miRNA datasets from 11 eukaryotic species.
• Demonstration of miRViz capabilities using real-case applications and reproducible datasets.

Main Results:

• MiRViz enables rapid identification of miRNA families, such as the miRNA-320 family in colon cancer exosomes.
• The tool visually highlights miRNA groups associated with pluripotency in breast cancer stem cells.
• MiRViz supports the interpretation of complex miRNA expression data for biological insights.

Conclusions:

• MiRViz simplifies the interpretation of large miRNA datasets for biologists.
• The tool facilitates hypothesis generation and data sharing in miRNA research.
• MiRViz aids in identifying biologically relevant miRNA groups, advancing cancer research.