mirTarVis

mirTarVis predicts and visualizes microRNA (miRNA)–mRNA interactions from miRNA and mRNA expression profile data to support discovery of regulatory relationships.

Key Features:

• Predictive Algorithms: Employs Bayesian inference, MINE (Maximal Information-based Nonparametric Exploration), correlation analyses, and mutual information analyses to predict miRNA targets.
• Sequence and Expression Integration: Integrates sequence complementarity information with miRNA and mRNA expression profile data to improve target prediction specificity.
• Data Processing and Filtering: Supports loading of miRNA and mRNA expression profiles and filtering of results prior to prediction and visualization.
• Treemap Visualization: Provides treemap representations to explore miRNA–target interaction networks in a hierarchical manner.
• Node-Link Diagrams: Provides node-link network diagrams for detailed analysis of predicted miRNA–mRNA interactions.

Scientific Applications:

• miRNA–mRNA interaction studies: Enables identification and exploration of putative miRNA targets from paired expression datasets.
• Gene regulation analysis: Supports investigation of regulatory relationships mediated by miRNAs using statistical association measures.
• Disease-focused case studies: Can be applied to expression-profile-based studies such as analysis of miRNA targets in asthma patient datasets.

Methodology:

Combines Bayesian inference, MINE, correlation analyses, and mutual information analyses to predict miRNA targets by integrating sequence complementarity with miRNA and mRNA expression profile data.