ComiR

ComiR predicts combinatorial microRNA (miRNA) targets within messenger RNA (mRNA) 3' untranslated regions (UTRs) across humans, mice, fruit flies, and worms to assess the regulatory impact of multiple miRNAs on mRNA expression.

Key Features:

• Combinatorial Prediction: Evaluates the collective targeting potential of multiple miRNAs acting together on a given mRNA.
• Thermodynamic and Machine Learning Integration: Combines thermodynamic modeling with machine learning algorithms to improve prediction accuracy.
• miRNA Expression Integration: Incorporates user-provided miRNA expression levels to weight predictions across samples.
• 3' UTR–Focused Cross‑Species Targeting: Assesses miRNA interactions specifically within mRNA 3' UTRs across humans, mice, fruit flies, and worms.
• Probability-Based Scoring: Produces probability scores per gene indicating the likelihood of being a functional target of the specified miRNA set.

Scientific Applications:

• Gene Regulation Analysis: Investigates post-transcriptional control by miRNAs and their combined effects on mRNA expression.
• Functional miRNA Studies: Identifies candidate mRNA targets influenced by combinatorial miRNA activity in biological processes and disease states.
• Regulatory Network Elucidation: Aids in mapping complex miRNA–mRNA regulatory networks driven by multiple miRNAs.
• Comparative Model Organism Studies: Enables cross-species comparison of miRNA–mRNA interactions in humans, mice, fruit flies, and worms.

Methodology:

ComiR integrates thermodynamic modeling with machine learning algorithms and incorporates user-supplied miRNA expression levels to predict combinatorial targeting on mRNA 3' UTRs.