An efficient algorithm for exploring RNA branching conformations under the nearest-neighbor thermodynamic model

Our results support the hypothesis that the conventional choice of multiloop parameters may limit prediction accuracy and that exploring alternative parameterizations is both tractable and worthwhile. The efficient partitioning algorithm we introduce makes this exploration feasible for longer sequences and larger datasets. Furthermore, we identify several open challenges in identifying the optimal structure.

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Publication Details

Journal
Algorithms for Molecular Biology
Published
2026-03-28
DOI
https://doi.org/10.1186/s13015-025-00296-4
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
0.00
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article

An efficient algorithm for exploring RNA branching conformations under the nearest-neighbor thermodynamic model

Christine Heitsch, Svetlana Poznanović, Owen Cardwell
Algorithms for Molecular Biology
RNA and protein synthesis mechanisms
article

An efficient algorithm for exploring RNA branching conformations under the nearest-neighbor thermodynamic model

Christine Heitsch, Svetlana Poznanović, Owen Cardwell
article en

Abstract

Our results support the hypothesis that the conventional choice of multiloop parameters may limit prediction accuracy and that exploring alternative parameterizations is both tractable and worthwhile. The efficient partitioning algorithm we introduce makes this exploration feasible for longer sequences and larger datasets. Furthermore, we identify several open challenges in identifying the optimal structure.

Algorithms for Molecular Biology
Georgia Institute of Technology (US), University of Bonn (DE), Clemson University (US)
Openalex Percentile: Top 5%
RNA and protein synthesis mechanisms
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An efficient algorithm for exploring RNA branching conformations under the nearest-neighbor thermodynamic model — Christine Heitsch, Svetlana Poznanović, et al. · Algorithms for Molecular Biology (2026) | TGRS Research Map | TGRS