RNAstructure: software for RNA secondary structure prediction and analysis

By Jessica S. Reuter, D. Mathews. BMC Bioinformatics, 2010

1,919 citations recorded by the source corpus.

BackgroundTo understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence.ResultsRNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained.ConclusionThe extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

Subfields: Molecular Biology, Organic Chemistry

View Paper: https://www.semanticscholar.org/paper/48ca3babc1bd11dbc1e41cf55a3e9b011d6bda3d

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Citations in the corpus

Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions (2022, methodology): “Thermodynamic-based methods are later improved by considering parameters of local structures, including experimental parameters (such as RNAstructure [21], RNAfold [22], RNAshapes [23]) and machine learning parameters (such as ContextFold [24], CONTRAfold [25], CentroidFold [26]).”
Advancing RNA 3D Structure Prediction: Exploring Hierarchical and Hybrid Approaches in CASP15 (2023, methodology): “Established models such as Vfold2D, 14 – 18 Mfold, 19 RNAFold, 20,21 and RNAstructure 22 have been applied to various 2D structure prediction tasks and have become benchmarks for machine-learning based methods in the field.”
UFold: fast and accurate RNA secondary structure prediction with deep learning (2020, neutral): “…together with the results of a collection of traditional energy-based, including Con-textfold (52), Contrafold (21), Linearfold (25), Eternafold (53), RNAfold (18), RNAStructure (Fold) (54), RNAsoft (55) and Mfold (19), and recent learning-based methods MXfold2 (41), SPOT-RNA (37) and e2efold (36).”
A bloom of Karlodinium australe (Gymnodiniales, Dinophyceae) associated with mass mortality of cage-cultured fishes in West Johor Strait, Malaysia (2014, neutral): “02 (Reuter and Mathews, 2010).”
RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures (2015, methodology): “Secondary structure (using the RNAStructure software) (Reuter and Mathews 2010) was adjusted using experimental data given for that RNA sequence by the Das group Additional information about potential pseudoknots or tertiary contacts was obtained from manual analysis of the mutate-and-map data…”
RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction. (2012, methodology): “…of predictive models for RNA secondary structure, pioneered by the seminal work of Tinoco and coworkers (Tinoco et al. 1973) and made commonly available in a number of tools that perform reasonably well for sequences of moderate size (Hofacker et al. 1994; Zuker 2003; Reuter and Mathews 2010); 2.”
Pervasive tertiary structure in the dengue virus RNA genome (2018, methodology): “6) and both 1M7 and differential SHAPE reactivities (using 1M6 and NMIA data) (6) was used to calculate a global partition function (10, 11), which yields base-pairing probabilities for all possible canonical base pairs.”
RNAstructure: web servers for RNA secondary structure prediction and analysis (2013, methodology): “CircleCompare (19) Compare two structures using overlaid circular plots to emphasize pairing differences and pseudoknots.”
RNA motif discovery by SHAPE and mutational profiling (SHAPE-MaP) (2014, neutral): “For sequences shorter than ~4,000 nucleotides and with sufficient read depth, the automated pipeline allows secondary structures to be automatically modeled using RNAstructure software, although this capability was not used for the RNAs in this work.”
ViennaRNA Package 2.0 (2011, methodology): “For each sequence, the MFE secondary structure was calculated with RNAfold 2.0, RNAfold 1.8.5, UNAFold 3.8 [19], and RNAstructure 5.2 [20].”
Automated 3D structure composition for large RNAs (2012, methodology): “3D structure of the 5S rRNA H. Marismortui 5S rRNA secondary structure was assigned using RNAstructure software (36) and chemical structure probing data (see ‘Materials and Methods’ section and Supplementary Figure S3) from SHAPE (37).”
Using Rosetta for RNA homology modeling (2019, methodology): “If an Rfam family or extensive sequence alignment is not available, tools for secondary structure prediction including RNAstructure (Reuter & Mathews, 2010), NUPACK (Dirks & Pierce, 2003), ViennaRNA (Lorenz et al., 2011), and CONTRAfold (Do, Woods, & Batzoglou, 2006) are appropriate although none…”
Modeling complex RNA tertiary folds with Rosetta. (2015, methodology): “RNAstructure (Reuter & Mathews, 2010) (http://rna.urmc.rochester.edu/ Figure 1 Workflow for modeling RNA structures in the Rosetta framework guided by experimental data.”
RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning (2019, methodology): “We downloaded the stand-alone version of mxfold 33 (available at https:// github.com/keio-bioinformatics/mxfold), ContextFold 16 (available at https://www. cs.bgu.ac.il/negevcb/contextfold/), CONTRAfold 14 (available at http://contra. stanford.edu/contrafold/), Knotty 24 (available at https://github”