miRACLe

miRACLe predicts individual-specific microRNA-mRNA interactions by integrating sequence characteristics and RNA expression profiles with a random contact model to improve target prediction for personalized analyses.

Key Features:

• Integration of sequence characteristics and expression profiles: Incorporates sequence characteristics and RNA expression profiles into a random contact model to estimate individual-specific probabilities of effective microRNA-mRNA contacts.
• Enhanced predictive power: Fits existing prediction tools such as TargetScan within its framework to improve their predictive accuracy, regulatory potential, and biological relevance.
• Robustness across biological contexts: Maintains performance across different biological contexts, types of expression data, and validation datasets.
• Efficiency and speed: Operates with computational efficiency suitable for large-scale analyses.
• Applicability to other algorithms: Can be applied to sequence-based algorithms including DIANA-microT-CDS, miRanda-mirSVR, and MirTarget4 to enhance their predictions.

Scientific Applications:

• miRNA target identification: Provides individual-specific predictions of microRNA-mRNA interactions to support target identification.
• Functional analysis of miRNAs: Enables assessment of miRNA regulatory potential and biological relevance in specific samples.
• Diagnostics and therapeutics: Supports discovery of miRNA biomarkers and therapeutic targets by improving target prediction accuracy relevant to diagnostics and therapeutics.
• Personalized medicine: Facilitates personalized-medicine approaches by tailoring miRNA-target predictions to individual RNA expression profiles.

Methodology:

Implements a random contact model that integrates sequence characteristics and RNA expression profiles and fits existing sequence-based prediction tools such as TargetScan, and can be applied to DIANA-microT-CDS, miRanda-mirSVR, and MirTarget4.