Circular RNAs and complex diseases: from experimental results to computational models

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Circular RNAs (circRNAs) are unique RNA molecules with diverse biological roles.
• circRNAs are implicated in the pathogenesis of various complex diseases.
• Accurate identification of circRNA-disease associations is vital for clinical applications.

Purpose of the Study:

• To review the discovery, classification, and functions of circRNAs.
• To highlight key diseases associated with circRNAs.
• To summarize computational models for predicting circRNA-disease associations.

Main Methods:

• Literature review of circRNA biology and disease associations.
• Compilation of relevant databases for circRNA annotation and validated associations.
• Categorization and analysis of computational prediction models (network-based and machine learning-based).

Main Results:

• Overview of circRNA characteristics and their involvement in four major diseases.
• Listing of accessible databases for circRNA resources.
• Introduction to state-of-the-art computational models and their evaluation methods.

Conclusions:

• Computational models offer powerful tools for predicting novel circRNA-disease links.
• Further development of models and data accumulation are essential for advancing circRNA research.
• This review provides a comprehensive resource for understanding circRNA-disease associations.