MSCFS

MSCFS infers functional similarity among circular RNAs (circRNAs) by integrating circRNA-disease associations, circRNA–gene–Gene Ontology (GO) associations, and circRNA sequence information to characterize circRNA functional relationships.

Key Features:

• Integration of Multiple Data Sources: MSCFS integrates circRNA-disease associations, circRNA–gene–Gene Ontology (GO) associations, and circRNA sequence information to capture multiple functional dimensions.
• Learning Representation Methods: Distinct representation learning techniques are applied to each data source to construct individual circRNA functional similarity networks.
• Network Integration: Individual functional similarity networks are combined into a comprehensive final circRNA functional similarity network.
• Performance Evaluation: Method performance is evaluated via correlation with circRNA-miRNA association similarity and circRNA co-expression similarity.
• Case Analysis Capability: The integrated network supports case analyses to infer novel potential functions and biological associations of circRNAs.

Scientific Applications:

• Function inference: Infer potential functions of circRNAs across biological contexts using computed functional similarities.
• Disease mechanism investigation: Analyze circRNA functional similarities with disease-associated entities to explore roles in disease mechanisms.
• Pathway and GO analysis: Explore Gene Ontology (GO) associations to provide insights into biological pathways and processes involving circRNAs.

Methodology:

Collect circRNA-disease links, circRNA–gene–GO associations, and sequence information; construct per-source functional similarity networks using representation learning methods; integrate these networks into a unified circRNA functional similarity network; validate via correlation analysis with circRNA-miRNA association similarity and circRNA co-expression similarity and apply case studies.