RNA Triplet Repeats: Improved Algorithms for Structure Prediction and Interactions - Département d'informatique
Pré-Publication, Document De Travail (Preprint/Prepublication) Année : 2024

RNA Triplet Repeats: Improved Algorithms for Structure Prediction and Interactions

Résumé

RNAs composed of Triplet Repeats (TR) have recently attracted much attention in the field of synthetic biology. We study the mimimum free energy (MFE) secondary structures of such RNAs and give improved algorithms to compute the MFE and the partition function. Furthermore, we study the interaction of multiple RNAs and design a new algorithm for computing MFE and partition function for RNA-RNA interactions, improving the previously known factorial running time to exponential. In the case of TR, we show computational hardness but still obtain a parameterized algorithm. Finally, we propose a polynomial-time algorithm for computing interactions from a base set of RNA strands and conduct experiments on the interaction of TR based on this algorithm. For instance, we study the probability that a base pair is formed between two strands with the same triplet pattern, allowing an assessment of a notion of orthogonality between TR.
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Dates et versions

hal-04766560 , version 1 (05-11-2024)

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  • HAL Id : hal-04766560 , version 1

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Boehmer Kimon, Sarah J. Berkemer, Sebastian Will, Yann Ponty. RNA Triplet Repeats: Improved Algorithms for Structure Prediction and Interactions. 2024. ⟨hal-04766560⟩
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