LinearCapR: Linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits

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ID: 317433
2026
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Abstract
MOTIVATION: RNA molecules adopt dynamic ensembles of secondary structures, where the local structural context of each nucleotide-such as whether it resides in a stem or a specific type of loop-strongly shapes molecular interactions and regulatory function. Structural-context probabilities therefore provide a more functionally informative view of RNA folding than the minimum free energy structures or base-pairing probabilities. However, existing tools either require O(N3) time or employ span-restricted approximations that omit long-range base-pairs, limiting their applicability to large and biologically important RNAs. RESULTS: We introduce LinearCapR, enabling linear-time, span-unrestricted computation of structural-context marginalized probabilities, using beam-pruned Stochastic Context Free Grammar-based computation. LinearCapR retains global ensemble features lost by span-limited methods and yields superior predictive power on bpRNA-1m(90) dataset, especially for multiloops and exterior regions, as well as long-distance stems. LinearCapR supports analysis of long RNAs, demonstrated on the full genome of SARS-CoV-2. LinearCapR provides the first base-pair-span-unrestricted, linear-time framework for RNA structural-context analysis, retaining key thermodynamic ensemble features essential for functional interpretation. It enables large-scale studies of viral genomes, long non-coding RNAs, and downstream analyses such as RNA-binding protein site prediction. AVAILABILITY AND IMPLEMENTATION: The source code of LinearCapR is available at https://github.com/hoget157/LinearCapR. The archived software release used in this work is available at Zenodo: https://doi.org/10.5281/zenodo.19450645. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W7164825342 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Takumi Otagaki, Hiroaki Hosokawa, Tsukasa Fukunaga, Junichi Iwakiri, Goro Terai, Kiyoshi Asai
Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag295
URL
https://doi.org/10.1093/bioinformatics/btag295
Keywords Keywords not found

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