DIANA-microT web server: elucidating microRNA functions through target prediction.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• MicroRNA (miRNA) target prediction is crucial for understanding miRNA functions in development and disease.
• Existing computational tools require user-friendly interfaces and robust validation methods.

Purpose of the Study:

• To introduce the DIANA-microT web server, an interface for the DIANA-microT 3.0 miRNA target prediction algorithm.
• To provide a comprehensive platform for exploring miRNA:target gene interactions and their functional implications.

Main Methods:

• Development of the DIANA-microT web server with a user-friendly interface.
• Integration of DIANA-microT 3.0 algorithm for miRNA target prediction.
• Incorporation of signal-to-noise ratio and precision scores for result evaluation.
• Validation using pSILAC-identified miRNA targets.

Main Results:

• DIANA-microT 3.0 achieved the highest ratio of correctly predicted targets (66%) among assessed programs.
• The web server offers extensive connectivity to biological databases and pathway information (KEGG).
• Users can search for targets using various nomenclatures and functional features.

Conclusions:

• The DIANA-microT web server provides a valuable resource for miRNA research.
• DIANA-microT 3.0 demonstrates high accuracy in computational miRNA target prediction.
• The platform facilitates the elucidation of miRNA functions in biological contexts.