BEAM web server: a tool for structural RNA motif discovery.

Area of Science:

• Computational Biology
• Bioinformatics
• Molecular Biology

Background:

• RNA structural motif finding is crucial but computationally challenging for high-throughput data.
• Existing tools struggle with the scale of datasets like eCLIP and PAR-CLIP, often containing thousands of RNA molecules.

Purpose of the Study:

• To introduce BEAM (BEAr Motifs finder), a novel web server for efficient RNA secondary structure motif discovery.
• To provide a scalable solution for analyzing tens of thousands of RNA molecules.

Main Methods:

• BEAM utilizes BEAR encoding to represent RNA secondary structures as strings, enabling rapid processing.
• It incorporates evolutionary information from the RFAM database via a substitution matrix for secondary structure elements.
• The web server automates RNA folding and encoding, offering user choice for folding programs.

Main Results:

• BEAM can analyze tens of thousands of RNA molecules to identify statistically significant RNA secondary structure motifs.
• The server provides an intuitive results page with motif logos, significance, graphical representations, and positional information.

Conclusions:

• BEAM offers a fast and efficient solution for RNA secondary structure motif discovery in large-scale datasets.
• The web server streamlines pre-processing and provides comprehensive results, advancing high-throughput RNA analysis.