FledFold

FledFold predicts RNA secondary structures by integrating thermodynamic stability and kinetic folding pathways to support inference of RNA structure–function relationships.

Key Features:

• Integrated thermodynamic and kinetic modeling: Combines thermodynamic stability calculations and kinetic folding pathway analysis to predict RNA secondary structures from primary sequences, improving accuracy particularly for RNAs without pseudoknots.
• Implementation: Implemented in C++.
• Output formats: Produces results in multiple output formats to facilitate integration into analysis workflows.

Scientific Applications:

• RNA structure–function studies: Enables analysis of RNA structural aspects to support research in molecular biology, genetics, and related fields.

Methodology:

Combines thermodynamic stability calculations and kinetic folding pathway analysis to predict RNA secondary structures from primary sequences; implemented in C++; runs on local PCs with Windows 7 or later and requires a minimum of 2 GB RAM.