ToppMiR

ToppMiR ranks microRNAs (miRs) and their messenger RNA (mRNA) targets by predicted functional impact within specific biological contexts using gene function-associated annotations and a machine learning-based analysis engine.

Key Features:

• Biologically centered co-analysis: Co-analyzes miRs and mRNAs using gene function-associated annotations to prioritize functional relevance rather than only physical binding strength.
• Machine learning-based analysis engine: Integrates annotations and feature data into machine learning models to score and evaluate miR–mRNA relationships.
• Contextual learning from gene-associated data: Learns biological context using gene-associated data derived from expression profiles or user-specified gene sets.
• Features association matrix: Calculates a features association matrix that incorporates biological functions, protein interactions, and other relevant features for scoring.
• Joint ranking system: Uses calculated scores to jointly rank candidate miRs and their corresponding mRNA targets by potential functional impact within the specified context.

Scientific Applications:

• Context-specific target prioritization: Identify and prioritize miRs and mRNA targets most likely to have functional impact in a given developmental, physiological, or disease context.
• Regulatory network inference: Reveal candidate regulatory relationships and networks involving miRs and mRNAs informed by functional annotations and protein interactions.
• Hypothesis-driven analyses: Test context-relevant hypotheses using expression-profile-derived or user-specified gene sets to inform miR–mRNA prioritization.

Methodology:

Co-analyzes miRs and mRNAs using gene function-associated annotations integrated into a machine learning-based analysis engine; learns biological context from expression profiles or user-specified genes; computes a features association matrix incorporating biological functions and protein interactions; scores and jointly ranks candidate miRs and mRNA targets by calculated functional-impact scores.