miRNet

miRNet facilitates statistical analysis and network-based functional interpretation of microRNA (miRNA) data generated by high-throughput experimental technologies.

Key Features:

• Comprehensive Knowledge Base: miRNet integrates miRNA-target interaction data from 11 distinct databases, including interactions with target genes, small molecules, long non-coding RNAs, epigenetic modifiers, and disease associations.
• Differential Expression Analysis Support: It supports differential expression analysis for microarray, RNA-seq, and quantitative PCR datasets.
• Network Visualization and Enrichment Analysis: miRNet provides graphical representation of miRNA interaction networks and enrichment analysis to identify associated biological pathways and processes.
• Statistical Analysis and Network-based Approaches: The framework supports statistical analysis and network-based approaches for functional interpretation of miRNA data.

Scientific Applications:

• Regulatory Network Elucidation: Constructing networks that link miRNAs to genes, small molecules, long non-coding RNAs, epigenetic modifiers, and disease associations to study regulatory roles.
• Functional and Pathway Analysis: Identifying collective functions and biological pathways associated with miRNA expression changes via enrichment analysis.
• Disease-related miRNA Research: Investigating miRNA dysregulation in complex diseases and pathological conditions.

Methodology:

miRNet integrates diverse interaction and expression datasets into a cohesive framework and applies statistical analysis, differential expression testing, network-based approaches, and enrichment analysis using high-quality interaction data.