ProbRNA

ProbRNA models high-throughput sequencing data from structure-probing experiments to extract structural features indicative of RNA secondary and tertiary structures.

Key Features:

• Statistical Modeling of Structure-Probing Data: Applies statistical modeling to data from reagents that cleave or mark nucleotides to infer local RNA structural properties.
• Feature Extraction and Prediction: Extracts structural features from probing data and predicts functional regions including yeast 'zipcodes' bound by the She complex.
• Enhanced Predictive Accuracy: Improves prediction accuracy compared with approaches that use only raw RNA probing signals or sequence features.
• Identification of RNA Binding Sites: Identifies RNA-binding protein sites using whole-transcriptome gPAR-CLIP (photoactivatable-ribonucleoside-enhanced cross-linking and immunopurification) data.

Scientific Applications:

• RNA Structure Analysis: Supports inference of RNA secondary and tertiary structures from structure-probing and sequencing data.
• Functional Genomics: Enables prediction of RNA localization signals ('zipcodes') and identification of protein-binding sites, informing studies of RNA localization and interactions such as those involving the She complex.
• Transcriptome-wide Studies: Integrates gPAR-CLIP and probing data to analyze RNA–protein interactions across entire transcriptomes for post-transcriptional regulation research.

Methodology:

Performs statistical modeling of structure-probing data from high-throughput sequencing, analyzes sequences marked or cleaved by specific reagents to extract structural features predictive of functional regions, and integrates gPAR-CLIP data for RNA-binding site identification.