GTfold

GTfold predicts RNA secondary structure using thermodynamic optimization adapted for parallel execution on multi-core processors to enable faster and accurate structure prediction.

Key Features:

• Speed and Scalability: Operates one to two orders of magnitude faster than de facto standard programs for RNA secondary structure prediction, enabling analysis of large and complex RNA sequences.
• Accuracy: Maintains accuracy comparable to UNAfold and RNAfold by implementing thermodynamic optimization techniques tailored for multi-core processors.
• Portability: Runs on a wide range of modern multi-core desktop machines, providing parallelized prediction outside specialized high-performance computing environments.

Scientific Applications:

• Large-scale RNA structural analysis: Enables prediction of secondary structures for long and complex RNAs, including viral genomes.
• Virology: Facilitates rapid analysis of lengthy viral genomes to support investigations of viral RNA structure.
• Basic molecular biology studies: Supports investigations into RNA structural biology in fundamental research contexts.
• Disease mechanisms and therapeutic development: Supports applied studies linking RNA structure to disease mechanisms and potential therapeutic strategies.

Methodology:

Thermodynamic optimization for RNA secondary structure prediction, implemented and optimized for parallel processing on multi-core systems.