miRetrieve

miRetrieve performs text mining of microRNA (miRNA) literature to extract, summarize, and compare miRNA–disease associations across biological contexts.

Key Features:

• R package implementation: Provided as an R package for computational access to its text-mining functionality.
• Literature text mining: Applies text-mining techniques to miRNA-related publications.
• Systematic extraction: Systematically extracts relevant information from a large corpus of publications.
• Data aggregation: Aggregates information from a vast array of publications into a consolidated dataset.
• Structured organization: Organizes extracted data to highlight connections between miRNAs and diseases.
• miRNA characterization and comparison: Enables characterization and comparison of miRNAs within specific disease contexts and across multiple areas.
• Cross-disease function identification: Identifies potential cross-disease functions of specific miRNAs.
• Hypothesis facilitation: Facilitates hypothesis generation based on organized literature-derived evidence.
• Demonstrated applicability: Applicability shown via an exemplary case study.

Scientific Applications:

• miRNA–disease association mapping: Map and summarize reported associations between miRNAs and diseases from the literature.
• Comparative analysis: Compare miRNA roles and reported findings across different disease fields.
• Cross-disease function discovery: Identify miRNAs with potential functions shared across multiple diseases.
• Hypothesis generation and prioritization: Inform and prioritize experimental hypotheses and study focus based on literature evidence.

Methodology:

Text mining of miRNA-related literature with systematic extraction and aggregation of relevant information from publications, implemented as an R package.