RNAscf

RNAscf predicts consensus RNA secondary structures from sets of unaligned RNA sequences to support structural characterization of non-coding RNAs.

Key Features:

• Consensus Folding Approach: Computes common secondary structures for multiple unaligned RNA sequences without requiring pre-aligned data.
• Sequence and Thermodynamics Integration: Leverages primary sequence information together with thermodynamic stability to improve prediction accuracy.
• Putative Stack Matching: Matches putative stacks within RNA sequences to integrate sequence data with structural predictions.

Scientific Applications:

• RNA Secondary Structure Prediction: Predicts consensus secondary structures to aid interpretation of RNA folding and potential functional motifs.
• Non-Coding RNA Research: Supports structural characterization and annotation of newly discovered non-coding RNAs.

Methodology:

Consensus folding of multiple unaligned RNA sequences without pre-alignment; integration of primary sequence information with thermodynamic stability assessments; matching of putative stacks to combine sequence and structural predictions; use of thermodynamic principles to evaluate energetic favorability.