Malysheva D, Dymova M, Richter V
Biophys Rev. 2025; 16(6):685-700.
PMID: 39830127
PMC: 11735759.
DOI: 10.1007/s12551-024-01252-z.
Qiu X
Biol Methods Protoc. 2025; 10(1):bpae097.
PMID: 39811444
PMC: 11729747.
DOI: 10.1093/biomethods/bpae097.
Zhu M, Zuber J, Tan Z, Sharma G, Mathews D
bioRxiv. 2024; .
PMID: 39464058
PMC: 11507696.
DOI: 10.1101/2024.10.12.618037.
Eich T, OLeary C, Moss W
NAR Genom Bioinform. 2024; 6(4):lqae143.
PMID: 39450312
PMC: 11500451.
DOI: 10.1093/nargab/lqae143.
Allan M, Aruda J, Plung J, Grote S, Martin des Taillades Y, de Lajarte A
Res Sq. 2024; .
PMID: 39149495
PMC: 11326378.
DOI: 10.21203/rs.3.rs-4814547/v1.
sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure.
Bugnon L, Di Persia L, Gerard M, Raad J, Prochetto S, Fenoy E
Brief Bioinform. 2024; 25(4).
PMID: 38855913
PMC: 11163250.
DOI: 10.1093/bib/bbae271.
RNA3DB: A structurally-dissimilar dataset split for training and benchmarking deep learning models for RNA structure prediction.
Szikszai M, Magnus M, Sanghi S, Kadyan S, Bouatta N, Rivas E
J Mol Biol. 2024; 436(17):168552.
PMID: 38552946
PMC: 11377173.
DOI: 10.1016/j.jmb.2024.168552.
Challenges and best practices in omics benchmarking.
Brooks T, Lahens N, Mrcela A, Grant G
Nat Rev Genet. 2024; 25(5):326-339.
PMID: 38216661
DOI: 10.1038/s41576-023-00679-6.
Comparative analysis of RNA secondary structure accuracy on predicted RNA 3D models.
Kulkarni M, Thangappan J, Deb I, Wu S
PLoS One. 2023; 18(9):e0290907.
PMID: 37656749
PMC: 10473517.
DOI: 10.1371/journal.pone.0290907.
Sequence similarity governs generalizability of de novo deep learning models for RNA secondary structure prediction.
Qiu X
PLoS Comput Biol. 2023; 19(4):e1011047.
PMID: 37068100
PMC: 10138783.
DOI: 10.1371/journal.pcbi.1011047.
How does precursor RNA structure influence RNA processing and gene expression?.
Herbert A, Hatfield A, Lackey L
Biosci Rep. 2023; 43(3).
PMID: 36689327
PMC: 9977717.
DOI: 10.1042/BSR20220149.
RAFFT: Efficient prediction of RNA folding pathways using the fast Fourier transform.
Opuu V, Merleau N, Messow V, Smerlak M
PLoS Comput Biol. 2022; 18(8):e1010448.
PMID: 36026505
PMC: 9455880.
DOI: 10.1371/journal.pcbi.1010448.
Deep learning models for RNA secondary structure prediction (probably) do not generalize across families.
Szikszai M, Wise M, Datta A, Ward M, Mathews D
Bioinformatics. 2022; 38(16):3892-3899.
PMID: 35748706
PMC: 9364374.
DOI: 10.1093/bioinformatics/btac415.
Getting to the bottom of lncRNA mechanism: structure-function relationships.
Sanbonmatsu K
Mamm Genome. 2021; 33(2):343-353.
PMID: 34642784
PMC: 8509902.
DOI: 10.1007/s00335-021-09924-x.
Targeting structural features of viral genomes with a nano-sized supramolecular drug.
Melidis L, Styles I, Hannon M
Chem Sci. 2021; 12(20):7174-7184.
PMID: 34123344
PMC: 8153246.
DOI: 10.1039/d1sc00933h.
Viral RNA structure analysis using DMS-MaPseq.
Tomezsko P, Swaminathan H, Rouskin S
Methods. 2020; 183:68-75.
PMID: 32251733
PMC: 7541462.
DOI: 10.1016/j.ymeth.2020.04.001.
Base-pair ambiguity and the kinetics of RNA folding.
Zhou G, Loper J, Geman S
BMC Bioinformatics. 2019; 20(1):666.
PMID: 31830902
PMC: 6909616.
DOI: 10.1186/s12859-019-3303-6.