miR_Path

miR_Path infers cancer-related microRNAs (miRNAs) from gene expression profiles to identify miRNAs associated with specific cancers without requiring matched miRNA expression datasets.

Key Features:

• Novel Computational Framework: Infers miRNA–cancer associations using only gene expression profiles, operating without matched miRNA and gene expression datasets.
• High Precision Identification: Demonstrates superior precision in identifying cancer-associated miRNAs, validated across multiple cancer datasets.
• Validation of Predictions: Some novel predictions are corroborated by differentially expressed miRNA data and literature evidence.
• Cancer-miRNA-Pathway Network Construction: Constructs cancer–miRNA–pathway networks to elucidate miRNA involvement in cancer-related pathways.

Scientific Applications:

• Cancer Research: Supports investigation of molecular mechanisms of tumorigenesis and progression and discovery of candidate biomarkers and therapeutic targets.
• Functional Characterization of miRNAs: Enables prioritization of miRNAs for functional studies by inferring relevant miRNAs directly from gene expression data.
• Pathway Analysis: Provides networks for exploring how miRNAs influence cellular pathways involved in cancer from a systems biology perspective.

Methodology:

Integrates gene expression data and analyzes the regulatory impact of miRNAs on gene expression patterns to infer miRNA–cancer associations, identifying candidate cancer-related miRNAs without requiring direct miRNA expression measurements.