Monte Carlo Inverse Folding
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 May 2020.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 2; 2025: 1; 2026: 1.
5 papers.
- 2024Learning a Prior for Monte Carlo Search by Replaying Solutions to Combinatorial Problemscited by 4
- 2024Generalized Nested Rollout Policy Adaptation with Limited Repetitionscited by 3
- 2022Nested Search versus Limited Discrepancy Searchcited by 0
- 2025Eterna is Solvedcited by 0
- 2026The Montparnasse Algorithm for RNA Designcited by 0
- 2026The Montparnasse Algorithm for RNA Design25 May 2026
- 2025Eterna is Solved4 May 2025
- 2024Learning a Prior for Monte Carlo Search by Replaying Solutions to Combinatorial Problems19 Jan 2024
- 2024Generalized Nested Rollout Policy Adaptation with Limited Repetitions18 Jan 2024
- 2022Nested Search versus Limited Discrepancy Search1 Oct 2022