Qiu X
Biol Methods Protoc. 2025; 10(1):bpae097.
PMID: 39811444
PMC: 11729747.
DOI: 10.1093/biomethods/bpae097.
Bernard C, Postic G, Ghannay S, Tahi F
Bioinformatics. 2025; 41(1).
PMID: 39775709
PMC: 11758789.
DOI: 10.1093/bioinformatics/btaf004.
Bahai A, Keong Kwoh C, Mu Y, Li Y
PLoS Comput Biol. 2025; 20(12):e1012715.
PMID: 39775239
PMC: 11723642.
DOI: 10.1371/journal.pcbi.1012715.
Bu F, Adam Y, Adamiak R, Antczak M, de Aquino B, Badepally N
Nat Methods. 2024; 22(2):399-411.
PMID: 39623050
PMC: 11810798.
DOI: 10.1038/s41592-024-02543-9.
Shen T, Hu Z, Sun S, Liu D, Wong F, Wang J
Nat Methods. 2024; 21(12):2287-2298.
PMID: 39572716
PMC: 11621015.
DOI: 10.1038/s41592-024-02487-0.
Advances and Challenges in Scoring Functions for RNA-Protein Complex Structure Prediction.
Zeng C, Zhuo C, Gao J, Liu H, Zhao Y
Biomolecules. 2024; 14(10).
PMID: 39456178
PMC: 11506084.
DOI: 10.3390/biom14101245.
Exploring the energetic and conformational properties of the sequence space connecting naturally occurring RNA tetraloop receptor motifs.
Shin J, Cuevas L, Roy R, Bonilla S, Al-Hashimi H, Greenleaf W
RNA. 2024; 30(12):1646-1659.
PMID: 39362695
PMC: 11571812.
DOI: 10.1261/rna.080039.124.
Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions.
Nithin C, Kmiecik S, Blaszczyk R, Nowicka J, Tuszynska I
Nucleic Acids Res. 2024; 52(13):7465-7486.
PMID: 38917327
PMC: 11260495.
DOI: 10.1093/nar/gkae541.
State-of-the-RNArt: benchmarking current methods for RNA 3D structure prediction.
Bernard C, Postic G, Ghannay S, Tahi F
NAR Genom Bioinform. 2024; 6(2):lqae048.
PMID: 38745991
PMC: 11091930.
DOI: 10.1093/nargab/lqae048.
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.
RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality.
Bernard C, Postic G, Ghannay S, Tahi F
Brief Bioinform. 2024; 25(2).
PMID: 38436560
PMC: 10939302.
DOI: 10.1093/bib/bbae064.
Machine learning in RNA structure prediction: Advances and challenges.
Zhang S, Li J, Chen S
Biophys J. 2024; 123(17):2647-2657.
PMID: 38297836
PMC: 11393687.
DOI: 10.1016/j.bpj.2024.01.026.
trRosettaRNA: automated prediction of RNA 3D structure with transformer network.
Wang W, Feng C, Han R, Wang Z, Ye L, Du Z
Nat Commun. 2023; 14(1):7266.
PMID: 37945552
PMC: 10636060.
DOI: 10.1038/s41467-023-42528-4.
Assessment of three-dimensional RNA structure prediction in CASP15.
Das R, Kretsch R, Simpkin A, Mulvaney T, Pham P, Rangan R
Proteins. 2023; 91(12):1747-1770.
PMID: 37876231
PMC: 10841292.
DOI: 10.1002/prot.26602.
Predicting 3D RNA structure from the nucleotide sequence using Euclidean neural networks.
Sha C, Wang J, Dokholyan N
Biophys J. 2023; 123(17):2671-2681.
PMID: 37838833
PMC: 11393712.
DOI: 10.1016/j.bpj.2023.10.011.
NuFold: A Novel Tertiary RNA Structure Prediction Method Using Deep Learning with Flexible Nucleobase Center Representation.
Kagaya Y, Zhang Z, Ibtehaz N, Wang X, Nakamura T, Huang D
bioRxiv. 2023; .
PMID: 37790488
PMC: 10542152.
DOI: 10.1101/2023.09.20.558715.
When will RNA get its AlphaFold moment?.
Schneider B, Sweeney B, Bateman A, cerny J, Zok T, Szachniuk M
Nucleic Acids Res. 2023; 51(18):9522-9532.
PMID: 37702120
PMC: 10570031.
DOI: 10.1093/nar/gkad726.
Advancing RNA 3D structure prediction: Exploring hierarchical and hybrid approaches in CASP15.
Li J, Zhang S, Chen S
Proteins. 2023; 91(12):1779-1789.
PMID: 37615235
PMC: 10841231.
DOI: 10.1002/prot.26583.
RNA 3D Structure Prediction: Progress and Perspective.
Wang X, Yu S, Lou E, Tan Y, Tan Z
Molecules. 2023; 28(14).
PMID: 37513407
PMC: 10386116.
DOI: 10.3390/molecules28145532.
The assessment of molecular dynamics results of three-dimensional RNA aptamer structure prediction.
Ropii B, Bethasari M, Anshori I, Koesoema A, Shalannanda W, Satriawan A
PLoS One. 2023; 18(7):e0288684.
PMID: 37498889
PMC: 10373999.
DOI: 10.1371/journal.pone.0288684.