TL;DR
This paper explores the application of various Monte Carlo Search algorithms to solve the RNA Inverse Folding problem, aiming to improve molecule design for biological and nanotechnological applications.
Contribution
It adapts and evaluates different Monte Carlo Search algorithms specifically for the RNA Inverse Folding problem, advancing computational methods in bioinformatics.
Findings
Nested Monte Carlo Search yields excellent results
Evaluation of multiple Monte Carlo algorithms for RNA folding
Potential improvements in RNA molecule design methods
Abstract
The RNA Inverse Folding problem comes from computational biology. The goal is to find a molecule that has a given folding. It is important for scientific fields such as bioengineering, pharmaceutical research, biochemistry, synthetic biology and RNA nanostructures. Nested Monte Carlo Search has given excellent results for this problem. We propose to adapt and evaluate different Monte Carlo Search algorithms for the RNA Inverse Folding problem.
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