List of RNA structure prediction software

This list of RNA structure prediction software is a compilation of software tools and web portals used for RNA structure prediction.

Single sequence secondary structure prediction.

Name	Description	Knots [Note 1]	Links	References
SQUARNA	Secondary structure prediction based on a greedy stem formation model	Yes	sourcecode	[1]
CentroidFold	Secondary structure prediction based on generalized centroid estimator	No	sourcecode webserver	[2]
CentroidHomfold	Secondary structure prediction by using homologous sequence information	No	sourcecode webserver	[3]
Context Fold	An RNA secondary structure prediction software based on feature-rich trained scoring models.	No	sourcecode webserver	[4]
CONTRAfold	Secondary structure prediction method based on conditional log-linear models (CLLMs), a flexible class of probabilistic models which generalize upon SCFGs by using discriminative training and feature-rich scoring.	No	sourcecode webserver	[5]
Crumple	Simple, cleanly written software to produce the full set of possible secondary structures for one sequence, given optional constraints.	No	sourcecode	[6]
CyloFold	Secondary structure prediction method based on placement of helices allowing complex pseudoknots.	Yes	webserver	[7]
E2Efold	A deep learning based method for efficiently predicting secondary structure by differentiating through a constrained optimization solver, without using dynamic programming.	Yes	sourcecode	[8] [9]
EternaFold	A multitask-learning-based model trained on data from the Eterna project.	No	sourcecode webserver	[10]
GTFold	Fast and scalable multicore code for predicting RNA secondary structure.	No	link sourcecode	[11]
INTERPIN	Algorithm and database for prediction of transcription termination sites in bacteria. Uses Mfold for RNA secondary structure prediction.	No	webserver	[12] [13]
IPknot	Fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming.	Yes	sourcecode webserver	[14]
KineFold	Folding kinetics of RNA sequences including pseudoknots by including an implementation of the partition function for knots.	Yes	linuxbinary, webserver	[15] [16]
Mfold	MFE (Minimum Free Energy) RNA structure prediction algorithm.	No	sourcecode, webserver	[17]
pKiss	A dynamic programming algorithm for the prediction of a restricted class (H-type and kissing hairpins) of RNA pseudoknots.	Yes	sourcecode, webserver	[18]
Pknots	A dynamic programming algorithm for optimal RNA pseudoknot prediction using the nearest neighbour energy model.	Yes	sourcecode	[19]
PknotsRG	A dynamic programming algorithm for the prediction of a restricted class (H-type) of RNA pseudoknots.	Yes	sourcecode, webserver	[20]
RNA123	Secondary structure prediction via thermodynamic-based folding algorithms and novel structure-based sequence alignment specific for RNA.	Yes	webserver
RNAfold	MFE RNA structure prediction algorithm. Includes an implementation of the partition function for computing basepair probabilities and circular RNA folding.	No	sourcecode, webserver	[17] [21] [22] [23] [24]
RNAshapes	MFE RNA structure prediction based on abstract shapes. Shape abstraction retains adjacency and nesting of structural features, but disregards helix lengths, thus reduces the number of suboptimal solutions without losing significant information. Furthermore, shapes represent classes of structures for which probabilities based on Boltzmann-weighted energies can be computed.	No	source & binaries, webserver	[25] [26]
RNAstructure	A program to predict lowest free energy structures and base pair probabilities for RNA or DNA sequences. Programs are also available to predict maximum expected accuracy structures and these can include pseudoknots. Structure prediction can be constrained using experimental data, including SHAPE, enzymatic cleavage, and chemical modification accessibility. Graphical user interfaces are available for Windows, Mac OS X, Linux. Programs are also available for use with Unix-style text interfaces. Also, a C++ class library is available.	Yes	source & binaries, webserver	[27] [28]
SARNA-Predict	RNA Secondary structure prediction method based on simulated annealing. It can also predict structure with pseudoknots.	Yes	link	[29]
seqfold	Predict the minimum free energy structure of nucleic acids. seqfold is an implementation of the Zuker, 1981 dynamic programming algorithm, the basis for UNAFold/mfold, with energy functions from SantaLucia, 2004 (DNA) and Turner, 2009 (RNA). MIT license. Python CLI or module.	No	link & source	[30]
Sfold	Statistical sampling of all possible structures. The sampling is weighted by partition function probabilities.	No	Github_Repository	[31] [32] [33] [34]
Sliding Windows & Assembly	Sliding windows and assembly is a tool chain for folding long series of similar hairpins.	No	sourcecode	[6]
SPOT-RNA	SPOT-RNA is first RNA secondary structure predictor which can predict all kind base pairs (canonical, noncanonical, pseudoknots, and base triplets).	Yes	sourcecode webserver	[35]
SwiSpot	Command-line utility for predicting alternative (secondary) configurations of riboswitches. It is based on the prediction of the so-called switching sequence, to subsequently constrain the folding of the two functional structures.	No	sourcecode	[36]
UFold	UFold: fast and accurate RNA secondary structure prediction with deep learning	Yes	sourcecode, webserver	[37]
UNAFold	Command-line utility for predicting alternative (secondary) configurations of riboswitches. It is based on the prediction of the so-called switching sequence, to subsequently constrain the folding of the two functional structures.	No	sourcecode	[38]
vsfold/vs subopt	Folds and predicts RNA secondary structure and pseudoknots using an entropy model derived from polymer physics. The program vs_subopt computes suboptimal structures based on the free energy landscape derived from vsfold5.	Yes	webserver	[39] [40]
Notes Knots: Pseudoknot prediction, <yes|no>.

Single sequence tertiary structure prediction

Name	Description	Knots [Note 1]	Links	References
trRosettaRNA	trRosettaRNA is an algorithm for automated prediction of RNA 3D structure. It builds the RNA structure by Rosetta energy minimization, with deep learning restraints from a transformer network (RNAformer). trRosettaRNA has been validated in blind tests, including CASP15 and RNA-Puzzles, which suggests that that the automated predictions by trRosettaRNA are competitive to the predictions by the top human groups on natural RNAs.	Yes	webserver sourcecode	[41]
BARNACLE	A Python library for the probabilistic sampling of RNA structures that are compatible with a given nucleotide sequence and that are RNA-like on a local length scale.	Yes	sourcecode	[42]
FARFAR2	Automated de novo prediction of native-like RNA tertiary structures .	Yes	webserver	[43]
iFoldRNA	three-dimensional RNA structure prediction and folding	Yes	webserver	[44]
MC-Fold MC-Sym Pipeline	Thermodynamics and Nucleotide cyclic motifs for RNA structure prediction algorithm. 2D and 3D structures.	Yes	sourcecode, webserver	[45]
NAST	Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters	Un­known	executables	[46]
MMB	Turning limited experimental information into 3D models of RNA	Un­known	sourcecode	[47]
RNA123	Integrated platform for de novo and homology modeling of RNA 3D structures, where coordinate file input, sequence editing, sequence alignment, structure prediction and analysis features are all accessed from one intuitive graphical user interface.	Yes
RNAComposer	Fully automated prediction of large RNA 3D structures.	Yes	webserver webserver	[48]
Notes Knots: Pseudoknot prediction, <yes|no>.

Comparative methods

The single sequence methods mentioned above have a difficult job detecting a small sample of reasonable secondary structures from a large space of possible structures. A good way to reduce the size of the space is to use evolutionary approaches. Structures that have been conserved by evolution are far more likely to be the functional form. The methods below use this approach.

Name	Description	Number of sequences [Note 1]	Alignment [Note 2]	Structure [Note 3]	Knots [Note 4]	Link	References
SQUARNA	Common secondary structure prediction based on a greedy stem formation model	any	No	Yes	Yes	sourcecode	[1]
Carnac	Comparative analysis combined with MFE folding.	any	No	Yes	No	sourcecode, webserver	[49] [50]
CentroidAlifold	Common secondary structure prediction based on generalized centroid estimator	any	No	Yes	No	sourcecode	[51]
CentroidAlign	Fast and accurate multiple aligner for RNA sequences	any	Yes	No	No	sourcecode	[52]
CMfinder	an expectation maximization algorithm using covariance models for motif description. Uses heuristics for effective motif search, and a Bayesian framework for structure prediction combining folding energy and sequence covariation.	${\displaystyle 3\leq seqs\leq 60}$	Yes	Yes	No	sourcecode, webserver, website	[53]
CONSAN	implements a pinned Sankoff algorithm for simultaneous pairwise RNA alignment and consensus structure prediction.	2	Yes	Yes	No	sourcecode	[54]
DAFS	Simultaneous aligning and folding of RNA sequences via dual decomposition.	any	Yes	Yes	Yes	sourcecode	[55]
Dynalign	an algorithm that improves the accuracy of structure prediction by combining free energy minimization and comparative sequence analysis to find a low free energy structure common to two sequences without requiring any sequence identity.	2	Yes	Yes	No	sourcecode	[56] [57] [58]
Foldalign	An algorithm capable of making both local and global pairwise structural alignments of RNAs. Based on a combination of energy minimization of the conserved structure and sequence similarity using ribosum-like scoring matrices. For local alignments more than one alignment can be returned.	2	Yes	Yes	No	sourcecode, webserver , website	[59]
FoldalignM	A multiple RNA structural RNA alignment method, to a large extent based on the PMcomp program.	any	Yes	Yes	No	sourcecode	[60]
FRUUT	A pairwise RNA structural alignment tool based on the comparison of RNA trees. Considers alignments in which the compared trees can be rooted differently (with respect to the standard "external loop" corresponding roots), and/or permuted with respect to branching order.	any	Yes	input	No	sourcecode, webserver	[61] [62]
GraphClust	Fast RNA structural clustering method of local RNA secondary structures. Predicted clusters are refined using LocARNA and CMsearch. Due to the linear time complexity for clustering it is possible to analyse large RNA datasets.	any	Yes	Yes	No	sourcecode	[63]
KNetFold	Computes a consensus RNA secondary structure from an RNA sequence alignment based on machine learning.	any	input	Yes	Yes	linuxbinary, webserver	[64]
LARA	Produce a global fold and alignment of ncRNA families using integer linear programming and Lagrangian relaxation.	any	Yes	Yes	No	sourcecode	[65]
LocaRNA	LocaRNA is the successor of PMcomp with an improved time complexity. It is a variant of Sankoff's algorithm for simultaneous folding and alignment, which takes as input pre-computed base pair probability matrices from McCaskill's algorithm as produced by RNAfold -p. Thus the method can also be viewed as way to compare base pair probability matrices.	any	Yes	Yes	No	sourcecode, webserver	[66]
MASTR	A sampling approach using Markov chain Monte Carlo in a simulated annealing framework, where both structure and alignment is optimized by making small local changes. The score combines the log-likelihood of the alignment, a covariation term and the basepair probabilities.	any	Yes	Yes	No	sourcecode	[67] [68]
Multilign	This method uses multiple Dynalign calculations to find a low free energy structure common to any number of sequences. It does not require any sequence identity.	any	Yes	Yes	No	sourcecode	[69]
Murlet	a multiple alignment tool for RNA sequences using iterative alignment based on Sankoff's algorithm with sharply reduced computational time and memory.	any	Yes	Yes	No	webserver	[70]
MXSCARNA	a multiple alignment tool for RNA sequences using progressive alignment based on pairwise structural alignment algorithm of SCARNA.	any	Yes	Yes	No	webserver sourcecode	[71]
pAliKiss	pAliKiss predicts RNA secondary structures for fixed RNA multiple sequence alignments, with special attention for pseudoknotted structures. This program is an offspring of the hybridization of RNAalishapes and pKiss.	any	input	Yes	Yes	webserver sourcecode	[18]
PARTS	A method for joint prediction of alignment and common secondary structures of two RNA sequences using a probabilistic model based on pseudo free energies obtained from precomputed base pairing and alignment probabilities.	2	Yes	Yes	No	sourcecode	[72]
Pfold	Folds alignments using a SCFG trained on rRNA alignments.	${\displaystyle \leq 40}$	input	Yes	No	webserver	[73] [74]
PETfold	Formally integrates both the energy-based and evolution-based approaches in one model to predict the folding of multiple aligned RNA sequences by a maximum expected accuracy scoring. The structural probabilities are calculated by RNAfold and Pfold.	any	input	Yes	No	sourcecode	[75]
PhyloQFold	Method that takes advantage of the evolutionary history of a group of aligned RNA sequences for sampling consensus secondary structures, including pseudoknots, according to their approximate posterior probability.	any	input	Yes	Yes	sourcecode	[76]
PMcomp/PMmulti	PMcomp is a variant of Sankoff's algorithm for simultaneous folding and alignment, which takes as input pre-computed base pair probability matrices from McCaskill's algorithm as produced by RNAfold -p. Thus the method can also be viewed as way to compare base pair probability matrices. PMmulti is a wrapper program that does progressive multiple alignments by repeatedly calling pmcomp	${\displaystyle 2\leq seqs\leq 6}$	Yes	Yes	No	sourcecode, webserver	[77]
RNAG	A Gibbs sampling method to determine a conserved structure and the structural alignment.	any	Yes	Yes	No	sourcecode	[78]
R-COFFEE	uses RNAlpfold to compute the secondary structure of the provided sequences. A modified version of T-Coffee is then used to compute the multiple sequence alignment having the best agreement with the sequences and the structures. R-Coffee can be combined with any existing sequence alignment method.	any	Yes	Yes	No	sourcecode, webserver	[79] [80]
TurboFold	This algorithm predicts conserved structures in any number of sequences. It uses probabilistic alignment and partition functions to map conserved pairs between sequences, and then iterates the partition functions to improve structure prediction accuracy	any	No	Yes	Yes	sourcecode	[81] [82]
R-scape	Verify conserved secondary structure by measuring covarying basepairs and their statistical significance compared to pure phylogeny. Will propose a most conserved ("optimized") one if no secondary structure is given.	any	input	Yes	Yes	home page	[83]
RNA123	Included structure based sequence alignment (SBSA) algorithm uses a novel suboptimal version of the Needleman-Wunsch global sequence alignment method that fully accounts for secondary structure in the template and query. It also uses two separate substitution matrices optimized for RNA helices and single stranded regions. The SBSA algorithm provides >90% accurate sequence alignments even for structures as large as bacterial 23S rRNA: ~2,800 nts.	any	Yes	Yes	Yes	webserver
RNAalifold	Folds precomputed alignments using mix of free-energy and covariation measures. Ships with the ViennaRNA Package.	any	input	Yes	No	homepage	[21] [84]
RNAalishapes	Tool for secondary structure prediction for precomputed alignments using a mix of free-energy and a covariation measures. Output can be sifted by the abstract shapes concept to focus on major difference in suboptimal results.	any	input	Yes	No	sourcecode, webserver	[85]
RNAcast	enumerates the near-optimal abstract shape space, and predicts as the consensus an abstract shape common to all sequences, and for each sequence, the thermodynamically best structure which has this abstract shape.	any	No	Yes	No	sourcecode, webserver	[86]
RNAforester	Compare and align RNA secondary structures via a "forest alignment" approach.	any	Yes	input	No	sourcecode, webserver	[87] [88]
RNAmine	Frequent stem pattern miner from unaligned RNA sequences is a software tool to extract the structural motifs from a set of RNA sequences.	any	No	Yes	No	webserver	[89]
RNASampler	A probabilistic sampling approach that combines intrasequence base pairing probabilities with intersequence base alignment probabilities. This is used to sample possible stems for each sequence and compare these stems between all pairs of sequences to predict a consensus structure for two sequences. The method is extended to predict the common structure conserved among multiple sequences by using a consistency-based score that incorporates information from all the pairwise structural alignments.	any	Yes	Yes	Yes	sourcecode	[90]
SCARNA	Stem Candidate Aligner for RNA (Scarna) is a fast, convenient tool for structural alignment of a pair of RNA sequences. It aligns two RNA sequences and calculates the similarities of them, based on the estimated common secondary structures. It works even for pseudoknotted secondary structures.	2	Yes	Yes	No	webserver	[91]
SimulFold	simultaneously inferring RNA structures including pseudoknots, alignments, and trees using a Bayesian MCMC framework.	any	Yes	Yes	Yes	sourcecode	[92]
Stemloc	a program for pairwise RNA structural alignment based on probabilistic models of RNA structure known as Pair stochastic context-free grammars.	any	Yes	Yes	No	sourcecode	[93]
StrAl	an alignment tool designed to provide multiple alignments of non-coding RNAs following a fast progressive strategy. It combines the thermodynamic base pairing information derived from RNAfold calculations in the form of base pairing probability vectors with the information of the primary sequence.	${\displaystyle \leq 50}$	Yes	No	No	sourcecode, webserver	[94]
TFold	A tool for predicting non-coding RNA secondary structures including pseudoknots. It takes in input an alignment of RNA sequences and returns the predicted secondary structure(s). It combines criteria of stability, conservation and covariation in order to search for stems and pseudoknots. Users can change different parameters values, set (or not) some known stems (if there are) which are taken into account by the system, choose to get several possible structures or only one, search for pseudoknots or not, etc.	any	Yes	Yes	Yes	webserver	[95]
WAR	a webserver that makes it possible to simultaneously use a number of state of the art methods for performing multiple alignment and secondary structure prediction for noncoding RNA sequences.	${\displaystyle 2\leq seqs\leq 50}$	Yes	Yes	No	webserver	[96]
Xrate	a program for analysis of multiple sequence alignments using phylogenetic grammars, that may be viewed as a flexible generalization of the "Pfold" program.	any	Yes	Yes	No	sourcecode	[97]
Alifreefold/AlifreefoldMulti	an alignment-free approach to predict secondary structure from homologous RNA sequences. It computes a representative structure from a set of homologous RNA sequences using sub-optimal secondary structures generated for each sequence. It is based on a vector representation of sub-optimal structures capturing structure conservation signals by weighting structural motifs according to their conservation across the sub-optimal structures.	>5	No	Yes	No	sourcecode sourcecode webserver	[98] [99]
Notes Number of sequences: <any|num>. Alignment: predicts an alignment, <input|yes|no>. Structure: predicts structure, <input|yes|no>. Knots: Pseudoknot prediction, <yes|no>.

RNA solvent accessibility prediction

Name (Year)	Description	Link	References
RNAsnap2 (2020)	RNAsnap2 uses a dilated convolutional neural network with evolutionary features generated from BLAST + INFERNAL (same as RNAsol) and predicted base-pairing probabilities from LinearPartition as an input for the prediction of RNA solvent accessibility. Also, the single-sequence version of RNAsnap2 can predict the solvent accessibility of a given input RNA sequence without using evolutionary information.	sourcecode webserver	[100]
RNAsol (2019)	RNAsol predictor uses a unidirectional LSTM deep learning algorithm with evolutionary information generated from BLASTN + INFERNAL and predicted secondary structure from RNAfold as an input for the prediction of RNA solvent accessibility.	sourcecode webserver	[101]
RNAsnap (2017)	RNAsnap predictor uses an SVM machine learning algorithm and evolutionary information generated from BLASTN as an input for the prediction of RNA solvent accessibility.	sourcecode	[102]

Intermolecular interactions: RNA-RNA

Many ncRNAs function by binding to other RNAs. For example, miRNAs regulate protein coding gene expression by binding to 3' UTRs, small nucleolar RNAs guide post-transcriptional modifications by binding to rRNA, U4 spliceosomal RNA and U6 spliceosomal RNA bind to each other forming part of the spliceosome and many small bacterial RNAs regulate gene expression by antisense interactions E.g. GcvB, OxyS and RyhB.

Name	Description	Intra-molecular structure	Comparative	Link	References
SQUARNA	SQUARNA predicts RNA secondary structure formed by several RNA sequences using a greedy stem formation model	Yes	Yes	sourcecode	[1]
RNApredator	RNApredator uses a dynamic programming approach to compute RNA-RNA interaction sites.	Yes	No	webserver	[103]
GUUGle	A utility for fast determination of RNA-RNA matches with perfect hybridization via A-U, C-G, and G-U base pairing.	No	No	webserver	[104]
IntaRNA	Efficient target prediction incorporating the accessibility of target sites.	Yes	No	sourcecode webserver	[105] [106] [107] [108] [109]
CopraRNA	Tool for sRNA target prediction. It computes whole genome predictions by mix of distinct whole genome IntaRNA predictions.	Yes	Yes	sourcecode webserver	[110] [106]
MINT	Automatic tool to analyze three-dimensional structures of RNA and DNA molecules, their full-atom molecular dynamics trajectories or other conformation sets (e.g. X-ray or NMR-derived structures). For each RNA or DNA conformation MINT determines the hydrogen bonding network resolving the base pairing patterns, identifies secondary structure motifs (helices, junctions, loops, etc.) and pseudoknots. Also estimates the energy of stacking and phosphate anion-base interactions.	Yes	No	sourcecode webserver	[111]
NUPACK	Computes the full unpseudoknotted partition function of interacting strands in dilute solution. Calculates the concentrations, mfes, and base-pairing probabilities of the ordered complexes below a certain complexity. Also computes the partition function and basepairing of single strands including a class of pseudoknotted structures. Also enables design of ordered complexes.	Yes	No	NUPACK	[112]
OligoWalk/RNAstructure	Predicts bimolecular secondary structures with and without intramolecular structure. Also predicts the hybridization affinity of a short nucleic acid to an RNA target.	Yes	No		[113]
piRNA	Calculates the partition function and thermodynamics of RNA-RNA interactions. It considers all possible joint secondary structure of two interacting nucleic acids that do not contain pseudoknots, interaction pseudoknots, or zigzags.	Yes	No	linuxbinary	[114]
piRNAPred	an integrated framework for piRNA prediction employing hybrid features like k-mer nucleotide composition, secondary structure, thermodynamic and physicochemical properties.	Yes	No		[115]
RNAripalign	Calculates the partition function and thermodynamics of RNA-RNA interactions based on structural alignments. Also supports RNA-RNA interaction prediction for single sequences. It outputs suboptimal structures based on Boltzmann distribution. It considers all possible joint secondary structure of two interacting nucleic acids that do not contain pseudoknots, interaction pseudoknots, or zigzags.	Yes	No		[116]
RactIP	Fast and accurate prediction of RNA-RNA interaction using integer programming.	Yes	No	sourcecode webserver	[117]
RNAaliduplex	Based on RNAduplex with bonuses for covarying sites	No	Yes	sourcecode	[21]
RNAcofold	Works much like RNAfold, but allows specifying two RNA sequences which are then allowed to form a dimer structure.	Yes	No	sourcecode	[21] [118]
RNAduplex	Computes optimal and suboptimal secondary structures for hybridization. The calculation is simplified by allowing only inter-molecular base pairs.	No	No	sourcecode	[21]
RNAhybrid	Tool to find the minimum free energy hybridisation of a long and a short RNA (≤ 30 nt).	No	No	sourcecode, webserver	[119] [120]
RNAup	Calculates the thermodynamics of RNA-RNA interactions. RNA-RNA binding is decomposed into two stages. (1) First the probability that a sequence interval (e.g. a binding site) remains unpaired is computed. (2) Then the binding energy given that the binding site is unpaired is calculated as the optimum over all possible types of bindings.	Yes	No	sourcecode	[21] [121]

Intermolecular interactions: MicroRNA:any RNA

The below table includes interactions that are not limited to UTRs.

Name	Description	Cross-species	Intra-molecular structure	Comparative	Link	References
comTAR	A a web tool for the prediction of miRNA targets that is mainly based on the conservation of the potential regulation in plant species.	Yes	No	No	Web tool	[122]
RNA22	The first link (precomputed predictions) provides RNA22 predictions for all protein coding transcripts in human, mouse, roundworm, and fruit fly. It allows visualizing the predictions within a cDNA map and also find transcripts where multiple miR's of interest target. The second web-site link (interactive/custom sequences) first finds putative microRNA binding sites in the sequence of interest, then identifies the targeted microRNA. Both tools are provided by the Computational Medicine Center at Thomas Jefferson University.	Yes	No	No	precomputed predictions interactive/custom sequences	[123]
RNAhybrid	Tool to find the minimum free energy hybridisation of a long and a short RNA (≤ 30 nt).	Yes	No	No	sourcecode, webserver	[119] [120]
miRBooking	Simulates the stochiometric mode of action of microRNAs using a derivative of the Gale-Shapley algorithm for finding a stable set of duplexes. It uses quantifications for traversing the set of mRNA and microRNA pairs and seed complementarity for ranking and assigning sites.	Yes	No	No	sourcecode, webserver	[124]

Intermolecular interactions: MicroRNA:UTR

MicroRNAs regulate protein coding gene expression by binding to 3' UTRs, there are tools specifically designed for predicting these interactions. For an evaluation of target prediction methods on high-throughput experimental data see (Baek et al., Nature 2008), ^[125] (Alexiou et al., Bioinformatics 2009), ^[126] or (Ritchie et al., Nature Methods 2009) ^[127]

Name	Description	Cross-species	Intra-molecular structure	Comparative	Link	References
Cupid	Method for simultaneous prediction of miRNA-target interactions and their mediated competing endogenous RNA (ceRNA) interactions. It is an integrative approach significantly improves on miRNA-target prediction accuracy as assessed by both mRNA and protein level measurements in breast cancer cell lines. Cupid is implemented in 3 steps: Step 1: re-evaluate candidate miRNA binding sites in 3' UTRs. Step2: interactions are predicted by integrating information about selected sites and the statistical dependency between the expression profiles of miRNA and putative targets. Step 3: Cupid assesses whether inferred targets compete for predicted miRNA regulators.	human	No	Yes	software (MATLAB)	[128]
Diana-microT	Version 3.0 is an algorithm based on several parameters calculated individually for each microRNA and it combines conserved and non-conserved microRNA recognition elements into a final prediction score.	human, mouse	No	Yes	webserver	[129]
MicroTar	An animal miRNA target prediction tool based on miRNA-target complementarity and thermodynamic data.	Yes	No	No	sourcecode	[130]
miTarget	microRNA target gene prediction using a support vector machine.	Yes	No	No	webserver	[131]
miRror	Based on the notion of a combinatorial regulation by an ensemble of miRNAs or genes. miRror integrates predictions from a dozen of miRNA resources that are based on complementary algorithms into a unified statistical framework	Yes	No	No	webserver	[132] [133]
PicTar	Combinatorial microRNA target predictions.	8 vertebrates	No	Yes	predictions	[134]
PITA	Incorporates the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition.	Yes	Yes	No	executable, webserver, predictions	[135]
RNA22	The first link (precomputed predictions) provides RNA22 predictions for all protein coding transcripts in human, mouse, roundworm, and fruit fly. It allows visualizing the predictions within a cDNA map and also find transcripts where multiple miR's of interest target. The second web-site link (interactive/custom sequences) first finds putative microRNA binding sites in the sequence of interest, then identifies the targeted microRNA. Both tools are provided by the Computational Medicine Center at Thomas Jefferson University.	Yes	No	No	precomputed predictions interactive/custom sequences	[123]
RNAhybrid	Tool to find the minimum free energy hybridisation of a long and a short RNA (≤ 30 nt).	Yes	No	No	sourcecode, webserver	[119] [120]
Sylamer	Method to find significantly over or under-represented words in sequences according to a sorted gene list. Usually used to find significant enrichment or depletion of microRNA or siRNA seed sequences from microarray expression data.	Yes	No	No	sourcecode webserver	[136] [137]
TAREF	TARget REFiner (TAREF) predicts microRNA targets on the basis of multiple feature information derived from the flanking regions of the predicted target sites where traditional structure prediction approach may not be successful to assess the openness. It also provides an option to use encoded pattern to refine filtering.	Yes	No	No	server/sourcecode	[138]
p-TAREF	plant TARget REFiner (p-TAREF) identifies plant microRNA targets on the basis of multiple feature information derived from the flanking regions of the predicted target sites where traditional structure prediction approach may not be successful to assess the openness. It also provides an option to use encoded pattern to refine filtering. It first time employed power of machine learning approach with scoring scheme through support vector regression (SVR) while considering structural and alignment aspects of targeting in plants with plant specific models. p-TAREF has been implemented in concurrent architecture in server and standalone form, making it one of the very few available target identification tools able to run concurrently on simple desktops while performing huge transcriptome level analysis accurately and fast. Also provides option to experimentally validate the predicted targets, on the spot, using expression data, which has been integrated in its back-end, to draw confidence on prediction along with SVR score.p-TAREF performance benchmarking has been done extensively through different tests and compared with other plant miRNA target identification tools. p-TAREF was found to perform better.	Yes	No	No	server/standalone
TargetScan	Predicts biological targets of miRNAs by searching for the presence of sites that match the seed region of each miRNA. In flies and nematodes, predictions are ranked based on the probability of their evolutionary conservation. In zebrafish, predictions are ranked based on site number, site type, and site context, which includes factors that influence target-site accessibility. In mammals, the user can choose whether the predictions should be ranked based on the probability of their conservation or on site number, type, and context. In mammals and nematodes, the user can choose to extend predictions beyond conserved sites and consider all sites.	vertebrates, flies, nematodes	evaluated indirectly	Yes	sourcecode, webserver	[139] [140] [141] [142] [143] [144]

ncRNA gene prediction software

Name	Description	Number of sequences [Note 1]	Alignment [Note 2]	Structure [Note 3]	Link	References
Alifoldz	Assessing a multiple sequence alignment for the existence of an unusual stable and conserved RNA secondary structure.	any	input	Yes	sourcecode	[145]
EvoFold	a comparative method for identifying functional RNA structures in multiple-sequence alignments. It is based on a probabilistic model-construction called a phylo-SCFG and exploits the characteristic differences of the substitution process in stem-pairing and unpaired regions to make its predictions.	any	input	Yes	linuxbinary	[146]
GraphClust	Fast RNA structural clustering method to identify common (local) RNA secondary structures. Predicted structural clusters are presented as alignment. Due to the linear time complexity for clustering it is possible to analyse large RNA datasets.	any	Yes	Yes	sourcecode	[63]
MSARi	heuristic search for statistically significant conservation of RNA secondary structure in deep multiple sequence alignments.	any	input	Yes	sourcecode	[147]
QRNA	This is the code from Elena Rivas that accompanies a submitted manuscript "Noncoding RNA gene detection using comparative sequence analysis". QRNA uses comparative genome sequence analysis to detect conserved RNA secondary structures, including both ncRNA genes and cis-regulatory RNA structures.	2	input	Yes	sourcecode	[148] [149]
RNAz	program for predicting structurally conserved and thermodynamic stable RNA secondary structures in multiple sequence alignments. It can be used in genome wide screens to detect functional RNA structures, as found in noncoding RNAs and cis-acting regulatory elements of mRNAs.	any	input	Yes	sourcecode, webserver RNAz 2	[150] [151] [152]
ScanFold	A program for predicting unique local RNA structures in large sequences with unusually stable folding.	1	None	Yes	sourcecode webserver	[153]
Xrate	a program for analysis of multiple sequence alignments using phylogenetic grammars, that may be viewed as a flexible generalization of the "Evofold" program.	any	Yes	Yes	sourcecode	[97]
Notes Number of sequences: <any|num>. Alignment: predicts an alignment, <input|yes|no>. Structure: predicts structure, <input|yes|no>.

Family specific gene prediction software

Name	Description	Family	Link	References
ARAGORN	ARAGORN detects tRNA and tmRNA in nucleotide sequences.	tRNA tmRNA	webserver source	[154]
miReader	miReader is a first of its type to detect mature miRNAs with no dependence on genomic or reference sequences. So far, discovering miRNAs was possible only with species for which genomic or reference sequences would be available as most of the miRNA discovery tools relied on drawing pre-miRNA candidates. Due to this, miRNA biology became limited to model organisms, mostly. miReader allows directly discerning mature miRNAs from small RNA sequencing data, with no need of genomic-reference sequences. It has been developed for many Phyla and species, from vertebrate to plant models. Its accuracy has been found to be consistently >90% in heavy validatory testing.	mature miRNA	webserver/source webserver/source	[155]
miRNAminer	Given a search query, candidate homologs are identified using BLAST search and then tested for their known miRNA properties, such as secondary structure, energy, alignment and conservation, in order to assess their fidelity.	MicroRNA	webserver	[156]
RISCbinder	Prediction of guide strand of microRNAs.	Mature miRNA	webserver	[157]
RNAmicro	A SVM-based approach that, in conjunction with a non-stringent filter for consensus secondary structures, is capable of recognizing microRNA precursors in multiple sequence alignments.	MicroRNA	homepage	[158]
RNAmmer	RNAmmer uses HMMER to annotate rRNA genes in genome sequences. Profiles were built using alignments from the European ribosomal RNA database [159] and the 5S Ribosomal RNA Database. [160]	rRNA	webserver source	[161]
SnoReport	Uses a mix of RNA secondary structure prediction and machine learning that is designed to recognize the two major classes of snoRNAs, box C/D and box H/ACA snoRNAs, among ncRNA candidate sequences.	snoRNA	sourcecode	[162]
SnoScan	Search for C/D box methylation guide snoRNA genes in a genomic sequence.	C/D box snoRNA	sourcecode, webserver	[163] [164]
tRNAscan-SE	a program for the detection of transfer RNA genes in genomic sequence.	tRNA	sourcecode, webserver	[164] [165]
miRNAFold	A fast ab initio software for searching for microRNA precursors in genomes.	microRNA	webserver	[166]

RNA homology search software

Name	Description	Link	References
DECIPHER (software)	FindNonCoding takes a pattern mining approach to capture the essential sequence motifs and hairpin loops representing a non-coding RNA family and quickly identify matches in genomes. FindNonCoding was designed for ease of use and accurately finds non-coding RNAs with a low false discovery rate.	sourcecode	[167]
ERPIN	"Easy RNA Profile IdentificatioN" is an RNA motif search program reads a sequence alignment and secondary structure, and automatically infers a statistical "secondary structure profile" (SSP). An original Dynamic Programming algorithm then matches this SSP onto any target database, finding solutions and their associated scores.	sourcecode webserver	[168] [169] [170]
Infernal	"INFERence of RNA ALignment" is for searching DNA sequence databases for RNA structure and sequence similarities. It is an implementation of a special case of profile stochastic context-free grammars called covariance models (CMs).	sourcecode	[171] [172] [173]
GraphClust	Fast RNA structural clustering method to identify common (local) RNA secondary structures. Predicted structural clusters are presented as alignment. Due to the linear time complexity for clustering it is possible to analyse large RNA datasets.	sourcecode	[63]
PHMMTS	"pair hidden Markov models on tree structures" is an extension of pair hidden Markov models defined on alignments of trees.	sourcecode, webserver	[174]
RaveNnA	A slow and rigorous or fast and heuristic sequence-based filter for covariance models.	sourcecode	[175] [176]
RSEARCH	Takes one RNA sequence with its secondary structure and uses a local alignment algorithm to search a database for homologous RNAs.	sourcecode	[177]
Structator	Ultra fast software for searching for RNA structural motifs employing an innovative index-based bidirectional matching algorithm combined with a new fast fragment chaining strategy.	sourcecode	[178]
RaligNAtor	Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns	sourcecode	[179]

Benchmarks

Name	Description	Structure [Note 1]	Alignment [Note 2]	Phylogeny	Links	References
BRalibase I	A comprehensive comparison of comparative RNA structure prediction approaches	Yes	No	No	data	[180]
BRalibase II	A benchmark of multiple sequence alignment programs upon structural RNAs	No	Yes	No	data	[181]
BRalibase 2.1	A benchmark of multiple sequence alignment programs upon structural RNAs	No	Yes	No	data	[182]
BRalibase III	A critical assessment of the performance of homology search methods on noncoding RNA	No	Yes	No	data	[183]
CompaRNA	An independent comparison of single-sequence and comparative methods for RNA secondary structure prediction	Yes	No	No	AMU mirror or IIMCB mirror	[184]
EternaBench	Database comprising the diverse high-throughput structural data gathered through the crowdsourced RNA design project Eterna	Yes	No	No	data
RNAconTest	A test of RNA multiple sequence alignments based entirely on known three dimensional RNA structures	Yes	Yes	No	data	[185]
Notes Structure: benchmarks structure prediction tools <yes|no>. Alignment: benchmarks alignment tools <yes|no>.

Alignment viewers, editors

Name	Description	Alignment [Note 1]	Structure [Note 2]	Link	References
4sale	A tool for Synchronous RNA Sequence and Secondary Structure Alignment and Editing	Yes	Yes	sourcecode	[186]
Colorstock, SScolor, Raton	Colorstock, a command-line script using ANSI terminal color; SScolor, a Perl script that generates static HTML pages; and Raton, an Ajax web application generating dynamic HTML. Each tool can be used to color RNA alignments by secondary structure and to visually highlight compensatory mutations in stems.	Yes	Yes	sourcecode	[187]
Integrated Genome Browser (IGB)	Multiple alignment viewer written in Java.	Yes	No	sourcecode	[188]
Jalview	Multiple alignment editor written in Java.	Yes	No	sourcecode	[189] [190]
RALEE	a major mode for the Emacs text editor. It provides functionality to aid the viewing and editing of multiple sequence alignments of structured RNAs.	Yes	Yes	sourcecode	[191]
SARSE	A graphical sequence editor for working with structural alignments of RNA.	Yes	Yes	sourcecode	[192]
Notes Alignment: view and edit an alignment, <yes|no>. Structure: view and edit structure, <yes|no>.

Inverse folding, RNA design

Name	Description	Link	References
	Single state design
EteRNA/EteRNABot	An RNA folding game that challenges players to make sequences that fold into a target RNA structure. The best sequences for a given puzzle are synthesized and their structures are probed through chemical mapping. The sequences are then scored by the data's agreement to the target structure and feedback is provided to the players. EteRNABot is a software implementation based on design rules submitted by EteRNA players.	EteRNA Game EteRNABot web server	[193]
RNAinverse	The ViennaRNA Package provides RNAinverse, an algorithm for designing sequences with desired structure.	Web Server	[21]
RNAiFold	A complete RNA inverse folding approach based on constraint programming and implemented using OR Tools which allows for the specification of a wide range of design constraints. The RNAiFold software provides two algorithms to solve the inverse folding problem: i) RNA-CPdesign explores the complete search space and ii) RNA-LNSdesign based on the large neighborhood search metaheuristic is suitable to design large structures. The software can also design interacting RNA molecules using RNAcofold of the ViennaRNA Package. A fully functional, earlier implementation using COMET is available.	Web Server Source Code	[194] [195] [196]
RNA-SSD/RNA Designer	The RNA-SSD (RNA Secondary Structure Designer) approach first assigns bases probabilistically to each position based probabilistic models. Subsequently, a stochastic local search is used to optimize this sequence. RNA-SSD is publicly available under the name of RNA Designer at the RNASoft web page	Web Server	[197]
INFO-RNA	INFO-RNA uses a dynamic programming approach to generate an energy optimized starting sequence that is subsequently further improved by a stochastic local search that uses an effective neighbor selection method.	Web Server Source Code	[198] [199]
RNAexinv	RNAexinv is an extension of RNAinverse to generate sequences that not only fold into a desired structure, but they should also exhibit selected attributes such as thermodynamic stability and mutational robustness. This approach does not necessarily outputs a sequence that perfectly fits the input structure, but a shape abstraction, i.e. it keeps the adjacency and nesting of structural elements, but disregards helix lengths and the exact number unpaired positions, of it.	Source Code	[200]
RNA-ensign	This approach applies an efficient global sampling algorithm to examine the mutational landscape under structural and thermodynamical constraints. The authors show that the global sampling approach is more robust, succeeds more often and generates more thermodynamically stable sequences than local approaches do.	Source Code	[201]
IncaRNAtion	Successor of RNA-ensign that can specifically design sequences with a specified GC content using a GC-weighted Boltzmann ensemble and stochastic backtracking	Source Code	[202]
DSS-Opt	Dynamics in Sequence Space Optimization (DSS-Opt) uses Newtonian dynamics in the sequence space, with a negative design term and simulated annealing to optimize a sequence such that it folds into the desired secondary structure.	Source Code	[203]
MODENA	This approach interprets RNA inverse folding as a multi-objective optimization problem and solves it using a genetic algorithm. In its extended version MODENA is able to design pseudoknotted RNA structures with the aid of IPknot.	Source Code	[204] [205]
ERD	Evolutionary RNA Design (ERD) can be used to design RNA sequences that fold into a given target structure. Any RNA secondary structure contains different structural components, each having a different length. Therefore, in the first step, the RNA subsequences (pools) corresponding to different components with different lengths are reconstructed. Using these pools, ERD reconstructs an initial RNA sequence which is compatible with the given target structure. Then ERD uses an evolutionary algorithm to improve the quality of the subsequences corresponding to the components. The major contributions of ERD are using the natural RNA sequences, a different method to evaluate the sequences in each population, and a different hierarchical decomposition of the target structure into smaller substructures.	Web Server Source Code	[206]
antaRNA	Uses an underlying ant colony foraging heuristic terrain modeling to solve the inverse folding problem. The designed RNA sequences show high compliance to input structural and sequence constraints. Most prominently, also the GC value of the designed sequence can be regulated with high precision. GC value distribution sampling of solution sets is possible and sequence domain specific definition of multiple GC values within one entity. Due to the flexible evaluation of the intermediate sequences using underlying programs such as RNAfold, pKiss, or also HotKnots and IPKnot, RNA secondary nested structures and also pseudoknot structures of H- and K-type are feasible to solve with this approach.	Web Server Source Code	[207] [208]
	Dual state design
switch.pl	The ViennaRNA Package provides a Perl script to design RNA sequences that can adopt two states. For instance RNA thermometer, which change their structural state depending on the environmental temperature, have been successfully designed using this program.	Man Page Source Code	[209]
RiboMaker	Intended to design small RNAs (sRNA) and their target mRNA's 5'UTR. The sRNA is designed to activate or repress protein expression of the mRNA. It is also possible to design just one of the two RNA components provided the other sequence is fixed.	Web Server Source Code	[210]
	Multi state design
RNAblueprint	This C++ library is based on the RNAdesign multiple target sampling algorithm. It brings a SWIG interface for Perl and Python which allows for an effortless integration into various tools. Therefore, multiple target sequence sampling can be combined with many optimization techniques and objective functions.	Source Code	[211]
RNAdesign	The underlying algorithm is based on a mix of graph coloring and heuristic local optimization to find sequences can adapt multiple prescribed conformations. The software can also use of RNAcofold to design interacting RNA sequence pairs.	Source Code [ permanent dead link ]	[212]
Frnakenstein	Frnakenstein applies a genetic algorithm to solve the inverse RNA folding problem.	Source Code	[213]
ARDesigner	The Allosteric RNA Designer (ARDesigner) is a web-based tool that solves the inverse folding problem by incorporating mutational robustness. Beside a local search the software has been equipped with a simulated annealing approach to effectively search for good solutions. The tool has been used to design RNA thermometer.	[ dead link ]	[214]

Notes

Secondary structure viewers, editors

Name	Description	Link	References
PseudoViewer	Automatically visualizing RNA pseudoknot structures as planar graphs.	webapp/binary	[215] [216] [217] [218]
RNA Movies	browse sequential paths through RNA secondary structure landscapes	sourcecode	[219] [220]
RNA-DV	RNA-DV aims at providing an easy-to-use GUI for visualizing and designing RNA secondary structures. It allows users to interact directly with the RNA structure and perform operations such as changing primary sequence content and connect/disconnect nucleotide bonds. It also integrates thermodynamic energy calculations including four major energy models. RNA-DV recognizes three input formats including CT, RNAML and dot bracket (dp).	sourcecode	[221]
RNA2D3D	Program to generate, view, and compare 3-dimensional models of RNA	binary	[222]
RNAstructure	RNAstructure has a viewer for structures in ct files. It can also compare predicted structures using the circleplot program. Structures can be output as postscript files.	sourcecode	[223]
RNAView/RnamlView	Use RNAView to automatically identify and classify the types of base pairs that are formed in nucleic acid structures. Use RnamlView to arrange RNA structures.	sourcecode	[224]
RILogo	Visualizes the intra-/intermolecular base pairing of two interacting RNAs with sequence logos in a planar graph.	web server / sourcecode	[225]
VARNA	A tool for the automated drawing, visualization and annotation of the secondary structure of RNA, initially designed as a companion software for web servers and databases	webapp/sourcecode	[226]
forna	A web based viewer for displaying RNA secondary structures using the force-directed graph layout provided by the d3.js visualization library. It is based on fornac, a javascript container for simply drawing a secondary structure on a web page.	webapp fornac source forna source	[227]
R2R	Program for drawing aesthetic RNA consensus diagrams with automated pair covariance recognition. Rfam uses this program both for drawing the human-annotated SS and the R-scape covariance-optimized structure.	source	[228]
RNAcanvas	A web app for drawing and exploring nucleic acid structures.	webapp	[229]
RNAscape	Geometric mapping algorithm for RNA 3D structure to 2D diagram production, which attempts to preserve tertiary interaction topology, provided through an interactive webserver with various customizability options.	webserver sourcecode	[230]

See also

• RNA
• Non-coding RNA
• RNA structure
• Comparison of nucleic acid simulation software
• Comparison of software for molecular mechanics modeling

References

1. DR Bohdan; GI Nikolaev; JM Bujnicki; EF Baulin (August 2023). "SQUARNA - an RNA secondary structure prediction method based on a greedy stem formation model". doi: 10.1101/2023.08.28.555103 .{{cite journal}}: Cite journal requires |journal= (help)
2. Hamada M, Kiryu H, Sato K, Mituyama T, Asai K (February 2009). "Prediction of RNA secondary structure using generalized centroid estimators". Bioinformatics. 25 (4): 465–473. doi: 10.1093/bioinformatics/btn601 . PMID   19095700.
3. Hamada M, Sato K, Kiryu H, Mituyama T, Asai K (June 2009). "Predictions of RNA secondary structure by combining homologous sequence information". Bioinformatics. 25 (12): i330–i338. doi:10.1093/bioinformatics/btp228. PMC   2687982 . PMID   19478007.
4. Zakov S, Goldberg Y, Elhadad M, Ziv-Ukelson M (November 2011). "Rich parameterization improves RNA structure prediction". Journal of Computational Biology. 18 (11): 1525–1542. Bibcode:2011LNCS.6577..546Z. doi:10.1089/cmb.2011.0184. PMID   22035327.
5. Do CB, Woods DA, Batzoglou S (July 2006). "CONTRAfold: RNA secondary structure prediction without physics-based models". Bioinformatics. 22 (14): e90–e98. doi: 10.1093/bioinformatics/btl246 . PMID   16873527.
6. Schroeder SJ, Stone JW, Bleckley S, Gibbons T, Mathews DM (July 2011). "Ensemble of secondary structures for encapsidated satellite tobacco mosaic virus RNA consistent with chemical probing and crystallography constraints". Biophysical Journal. 101 (1): 167–175. Bibcode:2011BpJ...101..167S. doi:10.1016/j.bpj.2011.05.053. PMC   3127170 . PMID   21723827.
7. Bindewald E, Kluth T, Shapiro BA (July 2010). "CyloFold: secondary structure prediction including pseudoknots". Nucleic Acids Research. 38 (Web Server issue): W368–W372. doi:10.1093/nar/gkq432. PMC   2896150 . PMID   20501603.
8. Chen X, Li Y, Umarov R, Gao X, Song L (2020). "RNA Secondary Structure Prediction By Learning Unrolled Algorithms". arXiv: 2002.05810 [cs.LG].
9. Chen, X., Li, Y., Umarov, R., Gao, X., and Song, L. RNAsecondary structure prediction by learning unrolled algorithms. In International Conference on Learning Representations, 2020. URL https://openreview.net/forum?id=S1eALyrYDH.
10. Wayment-Steele, Hannah K.; Kladwang, Wipapat; Strom, Alexandra I.; Lee, Jeehyung; Treuille, Adrien; Becka, Alex; Das, Rhiju (2022). "RNA secondary structure packages evaluated and improved by high-throughput experiments". Nature Methods. 19 (10): 1234–1242. doi: 10.1038/s41592-022-01605-0 . ISSN   1548-7105. PMC   9839360 . PMID   36192461.
11. Swenson MS, Anderson J, Ash A, Gaurav P, Sükösd Z, Bader DA, et al. (July 2012). "GTfold: enabling parallel RNA secondary structure prediction on multi-core desktops". BMC Research Notes. 5: 341. doi: 10.1186/1756-0500-5-341 . PMC   3748833 . PMID   22747589.
12. Gupta, Swati; Padmashali, Namrata; Pal, Debnath (November 2023). "INTERPIN: A repository for intrinsic transcription termination hairpins in bacteria". Biochimie. 214 (Pt B): 228–236. doi:10.1016/j.biochi.2023.07.018. PMID   37499897.
13. Gupta, Swati; Pal, Debnath (2021-08-10). "Clusters of hairpins induce intrinsic transcription termination in bacteria". Scientific Reports. 11 (1): 16194. Bibcode:2021NatSR..1116194G. doi:10.1038/s41598-021-95435-3. ISSN   2045-2322. PMC   8355165 . PMID   34376740.
14. Sato K, Kato Y, Hamada M, Akutsu T, Asai K (July 2011). "IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming". Bioinformatics. 27 (13): i85–i93. doi:10.1093/bioinformatics/btr215. PMC   3117384 . PMID   21685106.
15. Xayaphoummine A, Bucher T, Isambert H (July 2005). "Kinefold web server for RNA/DNA folding path and structure prediction including pseudoknots and knots". Nucleic Acids Research. 33 (Web Server issue): W605–W610. doi:10.1093/nar/gki447. PMC   1160208 . PMID   15980546.
16. Xayaphoummine A, Bucher T, Thalmann F, Isambert H (December 2003). "Prediction and statistics of pseudoknots in RNA structures using exactly clustered stochastic simulations". Proceedings of the National Academy of Sciences of the United States of America. 100 (26): 15310–15315. arXiv: physics/0309117 . Bibcode:2003PNAS..10015310X. doi: 10.1073/pnas.2536430100 . PMC   307563 . PMID   14676318.
17. Zuker M, Stiegler P (January 1981). "Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information". Nucleic Acids Research. 9 (1): 133–148. doi:10.1093/nar/9.1.133. PMC   326673 . PMID   6163133.
18. Theis C, Janssen S, Giegerich R (2010). "Prediction of RNA Secondary Structure Including Kissing Hairpin Motifs". In Moulton V, Singh M (eds.). Algorithms in Bioinformatics. Vol. 6293 (Lecture Notes in Computer Science ed.). Springer Berlin Heidelberg. pp. 52–64. doi: 10.1007/978-3-642-15294-8_5 . ISBN   978-3-642-15293-1.
19. Rivas E, Eddy SR (February 1999). "A dynamic programming algorithm for RNA structure prediction including pseudoknots". Journal of Molecular Biology. 285 (5): 2053–2068. arXiv: physics/9807048 . doi:10.1006/jmbi.1998.2436. PMID   9925784. S2CID   2228845.
20. Reeder J, Steffen P, Giegerich R (July 2007). "pknotsRG: RNA pseudoknot folding including near-optimal structures and sliding windows". Nucleic Acids Research. 35 (Web Server issue): W320–W324. doi:10.1093/nar/gkm258. PMC   1933184 . PMID   17478505.
21. Hofacker IL, Fontana W, Stadler PF, Bonhoeffer A, Tacker M, Schuster P (1994). "Fast Folding and Comparison of RNA Secondary Structures". Monatshefte für Chemie. 125 (2): 167–188. doi:10.1007/BF00818163. S2CID   19344304.
22. McCaskill JS (1990). "The equilibrium partition function and base pair binding probabilities for RNA secondary structure". Biopolymers. 29 (6–7): 1105–1119. doi:10.1002/bip.360290621. hdl: 11858/00-001M-0000-0013-0DE3-9 . PMID   1695107. S2CID   12629688.
23. Hofacker IL, Stadler PF (May 2006). "Memory efficient folding algorithms for circular RNA secondary structures". Bioinformatics. 22 (10): 1172–1176. doi: 10.1093/bioinformatics/btl023 . PMID   16452114.
24. Bompfünewerer AF, Backofen R, Bernhart SH, Hertel J, Hofacker IL, Stadler PF, Will S (January 2008). "Variations on RNA folding and alignment: lessons from Benasque". Journal of Mathematical Biology. 56 (1–2): 129–144. CiteSeerX   10.1.1.188.1420 . doi:10.1007/s00285-007-0107-5. PMID   17611759. S2CID   15637111.
25. Giegerich R, Voss B, Rehmsmeier M (2004). "Abstract shapes of RNA". Nucleic Acids Research. 32 (16): 4843–4851. doi:10.1093/nar/gkh779. PMC   519098 . PMID   15371549.
26. Voss B, Giegerich R, Rehmsmeier M (February 2006). "Complete probabilistic analysis of RNA shapes". BMC Biology. 4 (1): 5. doi: 10.1186/1741-7007-4-5 . PMC   1479382 . PMID   16480488.
27. Mathews DH, Disney MD, Childs JL, Schroeder SJ, Zuker M, Turner DH (May 2004). "Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure". Proceedings of the National Academy of Sciences of the United States of America. 101 (19): 7287–7292. Bibcode:2004PNAS..101.7287M. doi: 10.1073/pnas.0401799101 . PMC   409911 . PMID   15123812.
28. Mathews DH (August 2004). "Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization". RNA. 10 (8): 1178–1190. doi:10.1261/rna.7650904. PMC   1370608 . PMID   15272118.
29. Tsang HH, Wiese KC (2010). "SARNA-Predict: accuracy improvement of RNA secondary structure prediction using permutation-based simulated annealing". IEEE/ACM Transactions on Computational Biology and Bioinformatics. 7 (4): 727–740. doi:10.1109/TCBB.2008.97. PMID   21030739. S2CID   12095376.
30. seqfold, Lattice Automation, 2022-03-27, retrieved 2022-03-27
31. Ding Y, Lawrence CE (December 2003). "A statistical sampling algorithm for RNA secondary structure prediction". Nucleic Acids Research. 31 (24): 7280–7301. doi:10.1093/nar/gkg938. PMC   297010 . PMID   14654704.
32. Ding Y, Chan CY, Lawrence CE (July 2004). "Sfold web server for statistical folding and rational design of nucleic acids". Nucleic Acids Research. 32 (Web Server issue): W135–W141. doi:10.1093/nar/gkh449. PMC   441587 . PMID   15215366.
33. Ding Y, Chan CY, Lawrence CE (August 2005). "RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble". RNA. 11 (8): 1157–1166. doi:10.1261/rna.2500605. PMC   1370799 . PMID   16043502.
34. Chan CY, Lawrence CE, Ding Y (October 2005). "Structure clustering features on the Sfold Web server". Bioinformatics. 21 (20): 3926–3928. doi: 10.1093/bioinformatics/bti632 . PMID   16109749.
35. Singh J, Hanson J, Paliwal K, Zhou Y (November 2019). "RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning". Nature Communications. 10 (1): 5407. Bibcode:2019NatCo..10.5407S. doi:10.1038/s41467-019-13395-9. PMC   6881452 . PMID   31776342.
36. Barsacchi M, Novoa EM, Kellis M, Bechini A (November 2016). "SwiSpot: modeling riboswitches by spotting out switching sequences". Bioinformatics. 32 (21): 3252–3259. doi: 10.1093/bioinformatics/btw401 . hdl: 11568/817190 . PMID   27378291.
37. Fu L, Cao Y, Wu J, Peng Q, Nie Q, Xie X (February 2022). "UFold: fast and accurate RNA secondary structure prediction with deep learning". Nucleic Acids Research. 50 (3): 14. doi: 10.1093/nar/gkab1074 . PMC   8860580 . PMID   34792173.
38. Markham NR, Zuker M (2008). "UNAFold". Bioinformatics. Methods in Molecular Biology. Vol. 453. pp. 3–31. doi:10.1007/978-1-60327-429-6_1. ISBN   978-1-60327-428-9. PMID   18712296.
39. Dawson WK, Fujiwara K, Kawai G (September 2007). "Prediction of RNA pseudoknots using heuristic modeling with mapping and sequential folding". PLOS ONE. 2 (9): e905. Bibcode:2007PLoSO...2..905D. doi: 10.1371/journal.pone.0000905 . PMC   1975678 . PMID   17878940.
40. Dawson WK, Takai T, Ito N, Shimizu K, Kawai G (2014). "A new entropy model for RNA: part III. Is the folding free energy landscape of RNA funnel shaped?". Journal of Nucleic Acids Investigation. 5 (1): 2652. doi: 10.4081/jnai.2014.2652 .
41. Wang W, et al. (Nov 2023). "trRosettaRNA: automated prediction of RNA 3D structure with transformer network". Nature Communications. 14 (1): 7266. Bibcode:2023NatCo..14.7266W. doi:10.1038/s41467-023-42528-4. PMC   10636060 . PMID   37945552.
42. Frellsen J, Moltke I, Thiim M, Mardia KV, Ferkinghoff-Borg J, Hamelryck T (June 2009). "A probabilistic model of RNA conformational space". PLOS Computational Biology. 5 (6): e1000406. Bibcode:2009PLSCB...5E0406F. doi: 10.1371/journal.pcbi.1000406 . PMC   2691987 . PMID   19543381.
43. Watkins, Andrew Martin; Rangan, Ramya; Das, Rhiju (2020-08-04). "FARFAR2: Improved De Novo Rosetta Prediction of Complex Global RNA Folds". Structure. 28 (8): 963–976.e6. doi: 10.1016/j.str.2020.05.011 . ISSN   0969-2126. PMC   7415647 . PMID   32531203.
44. Sharma S, Ding F, Dokholyan NV (September 2008). "iFoldRNA: three-dimensional RNA structure prediction and folding". Bioinformatics. 24 (17): 1951–1952. doi:10.1093/bioinformatics/btn328. PMC   2559968 . PMID   18579566.
45. Parisien M, Major F (March 2008). "The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data". Nature. 452 (7183): 51–55. Bibcode:2008Natur.452...51P. doi:10.1038/nature06684. PMID   18322526. S2CID   4415777.
46. Jonikas MA, Radmer RJ, Laederach A, Das R, Pearlman S, Herschlag D, Altman RB (February 2009). "Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters". RNA. 15 (2): 189–199. doi:10.1261/rna.1270809. PMC   2924536 . PMID   19144906.
47. Flores SC, Altman RB (September 2010). "Turning limited experimental information into 3D models of RNA". RNA. 16 (9): 1769–1778. doi:10.1261/rna.2112110. PMC   2648710 . PMID   20651028.
48. Popenda M, Szachniuk M, Antczak M, Purzycka KJ, Lukasiak P, Bartol N, et al. (August 2012). "Automated 3D structure composition for large RNAs". Nucleic Acids Research. 40 (14): e112. doi:10.1093/nar/gks339. PMC   3413140 . PMID   22539264.
49. Perriquet O, Touzet H, Dauchet M (January 2003). "Finding the common structure shared by two homologous RNAs". Bioinformatics. 19 (1): 108–116. doi: 10.1093/bioinformatics/19.1.108 . PMID   12499300.
50. Touzet H, Perriquet O (July 2004). "CARNAC: folding families of related RNAs". Nucleic Acids Research. 32. 32 (Web Server issue): W142–W145. doi:10.1093/nar/gkh415. PMC   441553 . PMID   15215367.
51. Hamada M, Sato K, Asai K (January 2011). "Improving the accuracy of predicting secondary structure for aligned RNA sequences". Nucleic Acids Research. 39 (2): 393–402. doi:10.1093/nar/gkq792. PMC   3025558 . PMID   20843778.
52. Hamada M, Sato K, Kiryu H, Mituyama T, Asai K (December 2009). "CentroidAlign: fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score". Bioinformatics. 25 (24): 3236–3243. doi: 10.1093/bioinformatics/btp580 . PMID   19808876.
53. Yao Z, Weinberg Z, Ruzzo WL (February 2006). "CMfinder--a covariance model based RNA motif finding algorithm". Bioinformatics. 22 (4): 445–452. doi: 10.1093/bioinformatics/btk008 . PMID   16357030.
54. Dowell RD, Eddy SR (September 2006). "Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints". BMC Bioinformatics. 7 (1): 400. doi: 10.1186/1471-2105-7-400 . PMC   1579236 . PMID   16952317.
55. Sato K, Kato Y, Akutsu T, Asai K, Sakakibara Y (December 2012). "DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition". Bioinformatics. 28 (24): 3218–3224. doi: 10.1093/bioinformatics/bts612 . PMID   23060618.
56. Mathews DH, Turner DH (March 2002). "Dynalign: an algorithm for finding the secondary structure common to two RNA sequences". Journal of Molecular Biology. 317 (2): 191–203. doi:10.1006/jmbi.2001.5351. PMID   11902836.
57. Mathews DH (May 2005). "Predicting a set of minimal free energy RNA secondary structures common to two sequences". Bioinformatics. 21 (10): 2246–2253. doi: 10.1093/bioinformatics/bti349 . PMID   15731207.
58. Harmanci AO, Sharma G, Mathews DH (April 2007). "Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign". BMC Bioinformatics. 8 (1): 130. doi: 10.1186/1471-2105-8-130 . PMC   1868766 . PMID   17445273.
59. Sundfeld D, Havgaard JH, de Melo AC, Gorodkin J (April 2016). "Foldalign 2.5: multithreaded implementation for pairwise structural RNA alignment". Bioinformatics. 32 (8): 1238–1240. doi:10.1093/bioinformatics/btv748. PMC   4824132 . PMID   26704597.
60. Torarinsson E, Havgaard JH, Gorodkin J (April 2007). "Multiple structural alignment and clustering of RNA sequences". Bioinformatics. 23 (8): 926–932. doi: 10.1093/bioinformatics/btm049 . PMID   17324941.
61. Milo N, Zakov S, Katzenelson E, Bachmat E, Dinitz Y, Ziv-Ukelson M (2012). "RNA Tree Comparisons via Unrooted Unordered Alignments". Algorithms in Bioinformatics. Lecture Notes in Computer Science. Vol. 7534. pp. 135–148. doi:10.1007/978-3-642-33122-0_11. ISBN   978-3-642-33121-3.
62. Milo N, Zakov S, Katzenelson E, Bachmat E, Dinitz Y, Ziv-Ukelson M (April 2013). "Unrooted unordered homeomorphic subtree alignment of RNA trees". Algorithms for Molecular Biology. 8 (1): 13. doi: 10.1186/1748-7188-8-13 . PMC   3765143 . PMID   23590940.
63. Heyne S, Costa F, Rose D, Backofen R (June 2012). "GraphClust: alignment-free structural clustering of local RNA secondary structures". Bioinformatics. 28 (12): i224–i232. doi:10.1093/bioinformatics/bts224. PMC   3371856 . PMID   22689765.
64. Bindewald E, Shapiro BA (March 2006). "RNA secondary structure prediction from sequence alignments using a network of k-nearest neighbor classifiers". RNA. 12 (3): 342–352. doi:10.1261/rna.2164906. PMC   1383574 . PMID   16495232.
65. Bauer M, Klau GW, Reinert K (July 2007). "Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization". BMC Bioinformatics. 8 (1): 271. doi: 10.1186/1471-2105-8-271 . PMC   1955456 . PMID   17662141.
66. Will S, Reiche K, Hofacker IL, Stadler PF, Backofen R (April 2007). "Inferring noncoding RNA families and classes by means of genome-scale structure-based clustering". PLOS Computational Biology. 3 (4): e65. Bibcode:2007PLSCB...3...65W. doi: 10.1371/journal.pcbi.0030065 . PMC   1851984 . PMID   17432929.
67. Lindgreen S, Gardner PP, Krogh A (December 2006). "Measuring covariation in RNA alignments: physical realism improves information measures". Bioinformatics. 22 (24): 2988–2995. doi: 10.1093/bioinformatics/btl514 . PMID   17038338.
68. Lindgreen S, Gardner PP, Krogh A (December 2007). "MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing". Bioinformatics. 23 (24): 3304–3311. CiteSeerX   10.1.1.563.7072 . doi:10.1093/bioinformatics/btm525. PMID   18006551.
69. Xu Z, Mathews DH (March 2011). "Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequences". Bioinformatics. 27 (5): 626–632. doi:10.1093/bioinformatics/btq726. PMC   3042186 . PMID   21193521.
70. Kiryu H, Tabei Y, Kin T, Asai K (July 2007). "Murlet: a practical multiple alignment tool for structural RNA sequences". Bioinformatics. 23 (13): 1588–1598. doi: 10.1093/bioinformatics/btm146 . PMID   17459961.
71. Tabei Y, Kiryu H, Kin T, Asai K (January 2008). "A fast structural multiple alignment method for long RNA sequences". BMC Bioinformatics. 9 (1): 33. doi: 10.1186/1471-2105-9-33 . PMC   2375124 . PMID   18215258.
72. Harmanci AO, Sharma G, Mathews DH (April 2008). "PARTS: probabilistic alignment for RNA joinT secondary structure prediction". Nucleic Acids Research. 36 (7): 2406–2417. doi:10.1093/nar/gkn043. PMC   2367733 . PMID   18304945.
73. Knudsen B, Hein J (June 1999). "RNA secondary structure prediction using stochastic context-free grammars and evolutionary history". Bioinformatics. 15 (6): 446–454. doi: 10.1093/bioinformatics/15.6.446 . PMID   10383470.
74. Knudsen B, Hein J (July 2003). "Pfold: RNA secondary structure prediction using stochastic context-free grammars". Nucleic Acids Research. 31 (13): 3423–3428. doi:10.1093/nar/gkg614. PMC   169020 . PMID   12824339.
75. Seemann SE, Gorodkin J, Backofen R (November 2008). "Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments". Nucleic Acids Research. 36 (20): 6355–6362. doi:10.1093/nar/gkn544. PMC   2582601 . PMID   18836192.
76. Doose G, Metzler D (September 2012). "Bayesian sampling of evolutionarily conserved RNA secondary structures with pseudoknots". Bioinformatics. 28 (17): 2242–2248. doi: 10.1093/bioinformatics/bts369 . PMID   22796961.
77. Hofacker IL, Bernhart SH, Stadler PF (September 2004). "Alignment of RNA base pairing probability matrices". Bioinformatics. 20 (14): 2222–2227. doi: 10.1093/bioinformatics/bth229 . PMID   15073017.
78. Wei D, Alpert LV, Lawrence CE (September 2011). "RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences". Bioinformatics. 27 (18): 2486–2493. doi:10.1093/bioinformatics/btr421. PMC   3167047 . PMID   21788211.
79. Wilm A, Higgins DG, Notredame C (May 2008). "R-Coffee: a method for multiple alignment of non-coding RNA". Nucleic Acids Research. 36 (9): e52. doi:10.1093/nar/gkn174. PMC   2396437 . PMID   18420654.
80. Moretti S, Wilm A, Higgins DG, Xenarios I, Notredame C (July 2008). "R-Coffee: a web server for accurately aligning noncoding RNA sequences". Nucleic Acids Research. 36 (Web Server issue): W10–W13. doi:10.1093/nar/gkn278. PMC   2447777 . PMID   18483080.
81. Harmanci AO, Sharma G, Mathews DH (April 2011). "TurboFold: iterative probabilistic estimation of secondary structures for multiple RNA sequences". BMC Bioinformatics. 12 (1): 108. doi: 10.1186/1471-2105-12-108 . PMC   3120699 . PMID   21507242.
82. Seetin MG, Mathews DH (March 2012). "TurboKnot: rapid prediction of conserved RNA secondary structures including pseudoknots". Bioinformatics. 28 (6): 792–798. doi:10.1093/bioinformatics/bts044. PMC   3307117 . PMID   22285566.
83. Rivas E, Clements J, Eddy SR (January 2017). "A statistical test for conserved RNA structure shows lack of evidence for structure in lncRNAs". Nature Methods. 14 (1): 45–48. doi:10.1038/nmeth.4066. PMC   5554622 . PMID   27819659.
84. Hofacker IL, Fekete M, Stadler PF (June 2002). "Secondary structure prediction for aligned RNA sequences". Journal of Molecular Biology. 319 (5): 1059–1066. doi:10.1016/S0022-2836(02)00308-X. PMID   12079347.
85. Voss B (2006). "Structural analysis of aligned RNAs". Nucleic Acids Research. 34 (19): 5471–5481. doi:10.1093/nar/gkl692. PMC   1636479 . PMID   17020924.
86. Reeder J, Giegerich R (September 2005). "Consensus shapes: an alternative to the Sankoff algorithm for RNA consensus structure prediction". Bioinformatics. 21 (17): 3516–3523. doi: 10.1093/bioinformatics/bti577 . PMID   16020472.
87. Höchsmann M, Töller T, Giegerich R, Kurtz S (2003). "Local similarity in RNA secondary structures". Proceedings. IEEE Computer Society Bioinformatics Conference. 2: 159–168. PMID   16452790.
88. Höchsmann M, Voss B, Giegerich R (2004). "Pure multiple RNA secondary structure alignments: a progressive profile approach". IEEE/ACM Transactions on Computational Biology and Bioinformatics. 1 (1): 53–62. doi:10.1109/TCBB.2004.11. PMID   17048408. S2CID   692442.
89. Hamada M, Tsuda K, Kudo T, Kin T, Asai K (October 2006). "Mining frequent stem patterns from unaligned RNA sequences". Bioinformatics. 22 (20): 2480–2487. doi: 10.1093/bioinformatics/btl431 . PMID   16908501.
90. Xu X, Ji Y, Stormo GD (August 2007). "RNA Sampler: a new sampling based algorithm for common RNA secondary structure prediction and structural alignment". Bioinformatics. 23 (15): 1883–1891. doi: 10.1093/bioinformatics/btm272 . PMID   17537756.
91. Tabei Y, Tsuda K, Kin T, Asai K (July 2006). "SCARNA: fast and accurate structural alignment of RNA sequences by matching fixed-length stem fragments". Bioinformatics. 22 (14): 1723–1729. doi: 10.1093/bioinformatics/btl177 . PMID   16690634.
92. Meyer IM, Miklós I (August 2007). "SimulFold: simultaneously inferring RNA structures including pseudoknots, alignments, and trees using a Bayesian MCMC framework". PLOS Computational Biology. 3 (8): e149. Bibcode:2007PLSCB...3..149M. doi: 10.1371/journal.pcbi.0030149 . PMC   1941756 . PMID   17696604.
93. Holmes I (March 2005). "Accelerated probabilistic inference of RNA structure evolution". BMC Bioinformatics. 6 (1): 73. doi: 10.1186/1471-2105-6-73 . PMC   1090553 . PMID   15790387.
94. Dalli D, Wilm A, Mainz I, Steger G (July 2006). "STRAL: progressive alignment of non-coding RNA using base pairing probability vectors in quadratic time". Bioinformatics. 22 (13): 1593–1599. doi: 10.1093/bioinformatics/btl142 . PMID   16613908.
95. Engelen S, Tahi F (April 2010). "Tfold: efficient in silico prediction of non-coding RNA secondary structures". Nucleic Acids Research. 38 (7): 2453–2466. doi:10.1093/nar/gkp1067. PMC   2853104 . PMID   20047957.
96. Torarinsson E, Lindgreen S (July 2008). "WAR: Webserver for aligning structural RNAs". Nucleic Acids Research. 36 (Web Server issue): W79–W84. doi:10.1093/nar/gkn275. PMC   2447782 . PMID   18492721.
97. Klosterman PS, Uzilov AV, Bendaña YR, Bradley RK, Chao S, Kosiol C, et al. (October 2006). "XRate: a fast prototyping, training and annotation tool for phylo-grammars". BMC Bioinformatics. 7 (1): 428. doi: 10.1186/1471-2105-7-428 . PMC   1622757 . PMID   17018148.
98. academic.oup.com https://academic.oup.com/bioinformatics/article/34/13/i70/5045712 . Retrieved 2023-01-10.{{cite web}}: Missing or empty |title= (help)
99. academic.oup.com https://academic.oup.com/nargab/article/2/4/lqaa086/5940903 . Retrieved 2023-01-10.{{cite web}}: Missing or empty |title= (help)
100. Hanumanthappa AK, Singh J, Paliwal K, Singh J, Zhou Y (January 2021). "Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network". Bioinformatics. 36 (21): 5169–5176. doi: 10.1093/bioinformatics/btaa652 . hdl: 10072/399087 . PMID   33106872.
101. Sun S, Wu Q, Peng Z, Yang J (May 2019). "Enhanced prediction of RNA solvent accessibility with long short-term memory neural networks and improved sequence profiles". Bioinformatics. 35 (10): 1686–1691. doi:10.1093/bioinformatics/bty876. PMID   30321300.
102. Yang Y, Li X, Zhao H, Zhan J, Wang J, Zhou Y (January 2017). "Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction". RNA. 23 (1): 14–22. doi:10.1261/rna.057364.116. PMC   5159645 . PMID   27807179.
103. Eggenhofer F, Tafer H, Stadler PF, Hofacker IL (July 2011). "RNApredator: fast accessibility-based prediction of sRNA targets". Nucleic Acids Research. 39 (Web Server issue): W149–W154. doi:10.1093/nar/gkr467. PMC   3125805 . PMID   21672960.
104. Gerlach W, Giegerich R (March 2006). "GUUGle: a utility for fast exact matching under RNA complementary rules including G-U base pairing". Bioinformatics. 22 (6): 762–764. doi: 10.1093/bioinformatics/btk041 . PMID   16403789.
105. Mann M, Wright PR, Backofen R (July 2017). "IntaRNA 2.0: enhanced and customizable prediction of RNA-RNA interactions". Nucleic Acids Research. 45 (W1): W435–W439. doi:10.1093/nar/gkx279. PMC   5570192 . PMID   28472523.
106. Wright PR, Georg J, Mann M, Sorescu DA, Richter AS, Lott S, et al. (July 2014). "CopraRNA and IntaRNA: predicting small RNA targets, networks and interaction domains". Nucleic Acids Research. 42 (Web Server issue): W119–W123. doi:10.1093/nar/gku359. PMC   4086077 . PMID   24838564.
107. Busch A, Richter AS, Backofen R (December 2008). "IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions". Bioinformatics. 24 (24): 2849–2856. doi:10.1093/bioinformatics/btn544. PMC   2639303 . PMID   18940824.
108. Richter AS, Schleberger C, Backofen R, Steglich C (January 2010). "Seed-based INTARNA prediction combined with GFP-reporter system identifies mRNA targets of the small RNA Yfr1". Bioinformatics. 26 (1): 1–5. doi:10.1093/bioinformatics/btp609. PMC   2796815 . PMID   19850757.
109. Smith C, Heyne S, Richter AS, Will S, Backofen R (July 2010). "Freiburg RNA Tools: a web server integrating INTARNA, EXPARNA and LOCARNA". Nucleic Acids Research. 38 (Web Server issue): W373–W377. doi:10.1093/nar/gkq316. PMC   2896085 . PMID   20444875.
110. Wright PR, Richter AS, Papenfort K, Mann M, Vogel J, Hess WR, et al. (September 2013). "Comparative genomics boosts target prediction for bacterial small RNAs". Proceedings of the National Academy of Sciences of the United States of America. 110 (37): E3487–E3496. Bibcode:2013PNAS..110E3487W. doi: 10.1073/pnas.1303248110 . PMC   3773804 . PMID   23980183.
111. Górska A, Jasiński M, Trylska J (September 2015). "MINT: software to identify motifs and short-range interactions in trajectories of nucleic acids". Nucleic Acids Research. 43 (17): e114. doi:10.1093/nar/gkv559. PMC   4787793 . PMID   26024667.
112. Dirks RM, Bois JS, Schaeffer JM, Winfree E, Pierce NA (2007). "Thermodynamic Analysis of Interacting Nucleic Acid Strands". SIAM Review. 49 (1): 65–88. Bibcode:2007SIAMR..49...65D. CiteSeerX   10.1.1.523.4764 . doi:10.1137/060651100.
113. Mathews DH, Burkard ME, Freier SM, Wyatt JR, Turner DH (November 1999). "Predicting oligonucleotide affinity to nucleic acid targets". RNA. 5 (11): 1458–1469. doi:10.1017/S1355838299991148. PMC   1369867 . PMID   10580474.
114. Chitsaz H, Salari R, Sahinalp SC, Backofen R (June 2009). "A partition function algorithm for interacting nucleic acid strands". Bioinformatics. 25 (12): i365–i373. doi:10.1093/bioinformatics/btp212. PMC   2687966 . PMID   19478011.
115. Monga I, Banerjee I (November 2019). "Computational Identification of piRNAs Using Features Based on RNA Sequence, Structure, Thermodynamic and Physicochemical Properties". Current Genomics. 20 (7): 508–518. doi:10.2174/1389202920666191129112705. PMC   7327968 . PMID   32655289.
116. Li AX, Marz M, Qin J, Reidys CM (February 2011). "RNA-RNA interaction prediction based on multiple sequence alignments". Bioinformatics. 27 (4): 456–463. arXiv: 1003.3987 . doi:10.1093/bioinformatics/btq659. PMID   21134894. S2CID   6586629.
117. Kato Y, Sato K, Hamada M, Watanabe Y, Asai K, Akutsu T (September 2010). "RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming". Bioinformatics. 26 (18): i460–i466. doi:10.1093/bioinformatics/btq372. PMC   2935440 . PMID   20823308.
118. Bernhart SH, Tafer H, Mückstein U, Flamm C, Stadler PF, Hofacker IL (March 2006). "Partition function and base pairing probabilities of RNA heterodimers". Algorithms for Molecular Biology. 1 (1): 3. doi: 10.1186/1748-7188-1-3 . PMC   1459172 . PMID   16722605.
119. Rehmsmeier M, Steffen P, Hochsmann M, Giegerich R (October 2004). "Fast and effective prediction of microRNA/target duplexes". RNA. 10 (10): 1507–1517. doi:10.1261/rna.5248604. PMC   1370637 . PMID   15383676.
120. Krüger J, Rehmsmeier M (July 2006). "RNAhybrid: microRNA target prediction easy, fast and flexible". Nucleic Acids Research. 34 (Web Server issue): W451–W454. doi:10.1093/nar/gkl243. PMC   1538877 . PMID   16845047.
121. Mückstein U, Tafer H, Hackermüller J, Bernhart SH, Stadler PF, Hofacker IL (May 2006). "Thermodynamics of RNA-RNA binding". Bioinformatics. 22 (10): 1177–1182. doi: 10.1093/bioinformatics/btl024 . PMID   16446276.
122. Chorostecki U, Palatnik JF (July 2014). "comTAR: a web tool for the prediction and characterization of conserved microRNA targets in plants". Bioinformatics. 30 (14): 2066–2067. doi: 10.1093/bioinformatics/btu147 . hdl: 11336/29681 . PMID   24632500.
123. Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, et al. (September 2006). "A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes". Cell. 126 (6): 1203–1217. doi: 10.1016/j.cell.2006.07.031 . PMID   16990141.
124. Weill N, Lisi V, Scott N, Dallaire P, Pelloux J, Major F (August 2015). "MiRBooking simulates the stoichiometric mode of action of microRNAs". Nucleic Acids Research. 43 (14): 6730–6738. doi:10.1093/nar/gkv619. PMC   4538818 . PMID   26089388.
125. Baek D, Villén J, Shin C, Camargo FD, Gygi SP, Bartel DP (September 2008). "The impact of microRNAs on protein output". Nature. 455 (7209): 64–71. Bibcode:2008Natur.455...64B. doi:10.1038/nature07242. PMC   2745094 . PMID   18668037.
126. Alexiou P, Maragkakis M, Papadopoulos GL, Reczko M, Hatzigeorgiou AG (December 2009). "Lost in translation: an assessment and perspective for computational microRNA target identification". Bioinformatics. 25 (23): 3049–3055. doi: 10.1093/bioinformatics/btp565 . PMID   19789267.
127. Ritchie W, Flamant S, Rasko JE (June 2009). "Predicting microRNA targets and functions: traps for the unwary". Nature Methods. 6 (6): 397–398. doi:10.1038/nmeth0609-397. PMID   19478799. S2CID   205417583.
128. Chiu HS, Llobet-Navas D, Yang X, Chung WJ, Ambesi-Impiombato A, Iyer A, et al. (February 2015). "Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks". Genome Research. 25 (2): 257–267. doi:10.1101/gr.178194.114. PMC   4315299 . PMID   25378249.
129. Maragkakis M, Alexiou P, Papadopoulos GL, Reczko M, Dalamagas T, Giannopoulos G, et al. (September 2009). "Accurate microRNA target prediction correlates with protein repression levels". BMC Bioinformatics. 10 (1): 295. doi: 10.1186/1471-2105-10-295 . PMC   2752464 . PMID   19765283.
130. Thadani R, Tammi MT (December 2006). "MicroTar: predicting microRNA targets from RNA duplexes". BMC Bioinformatics. 7. 7 (Suppl 5): S20. doi: 10.1186/1471-2105-7-S5-S20 . PMC   1764477 . PMID   17254305.
131. Kim SK, Nam JW, Rhee JK, Lee WJ, Zhang BT (September 2006). "miTarget: microRNA target gene prediction using a support vector machine". BMC Bioinformatics. 7 (1): 411. doi: 10.1186/1471-2105-7-411 . PMC   1594580 . PMID   16978421.
132. Friedman Y, Naamati G, Linial M (August 2010). "MiRror: a combinatorial analysis web tool for ensembles of microRNAs and their targets". Bioinformatics. 26 (15): 1920–1921. doi: 10.1093/bioinformatics/btq298 . PMID   20529892.
133. Balaga O, Friedman Y, Linial M (October 2012). "Toward a combinatorial nature of microRNA regulation in human cells". Nucleic Acids Research. 40 (19): 9404–9416. doi:10.1093/nar/gks759. PMC   3479204 . PMID   22904063.
134. Krek A, Grün D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, et al. (May 2005). "Combinatorial microRNA target predictions". Nature Genetics. 37 (5): 495–500. doi:10.1038/ng1536. PMID   15806104. S2CID   22672750.
135. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E (October 2007). "The role of site accessibility in microRNA target recognition". Nature Genetics. 39 (10): 1278–1284. doi:10.1038/ng2135. PMID   17893677. S2CID   1721807.
136. van Dongen S, Abreu-Goodger C, Enright AJ (December 2008). "Detecting microRNA binding and siRNA off-target effects from expression data". Nature Methods. 5 (12): 1023–1025. doi:10.1038/nmeth.1267. PMC   2635553 . PMID   18978784.
137. Bartonicek N, Enright AJ (November 2010). "SylArray: a web server for automated detection of miRNA effects from expression data". Bioinformatics. 26 (22): 2900–2901. doi: 10.1093/bioinformatics/btq545 . PMID   20871108.
138. Heikham R, Shankar R (March 2010). "Flanking region sequence information to refine microRNA target predictions". Journal of Biosciences. 35 (1): 105–118. doi:10.1007/s12038-010-0013-7. PMID   20413915. S2CID   7047781.
139. Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB (December 2003). "Prediction of mammalian microRNA targets". Cell. 115 (7): 787–798. doi: 10.1016/S0092-8674(03)01018-3 . PMID   14697198.
140. Lewis BP, Burge CB, Bartel DP (January 2005). "Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets". Cell. 120 (1): 15–20. doi: 10.1016/j.cell.2004.12.035 . PMID   15652477.
141. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP (July 2007). "MicroRNA targeting specificity in mammals: determinants beyond seed pairing". Molecular Cell. 27 (1): 91–105. doi:10.1016/j.molcel.2007.06.017. PMC   3800283 . PMID   17612493.
142. Garcia DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP (September 2011). "Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs". Nature Structural & Molecular Biology. 18 (10): 1139–1146. doi:10.1038/nsmb.2115. PMC   3190056 . PMID   21909094.
143. Agarwal V, Bell GW, Nam JW, Bartel DP (August 2015). "Predicting effective microRNA target sites in mammalian mRNAs". eLife. 4: e05005. doi: 10.7554/eLife.05005 . PMC   4532895 . PMID   26267216.
144. Agarwal V, Subtelny AO, Thiru P, Ulitsky I, Bartel DP (October 2018). "Predicting microRNA targeting efficacy in Drosophila". Genome Biology. 19 (1): 152. doi: 10.1186/s13059-018-1504-3 . PMC   6172730 . PMID   30286781.
145. Washietl S, Hofacker IL (September 2004). "Consensus folding of aligned sequences as a new measure for the detection of functional RNAs by comparative genomics". Journal of Molecular Biology. 342 (1): 19–30. CiteSeerX   10.1.1.58.6251 . doi:10.1016/j.jmb.2004.07.018. PMID   15313604.
146. Pedersen JS, Bejerano G, Siepel A, Rosenbloom K, Lindblad-Toh K, Lander ES, et al. (April 2006). "Identification and classification of conserved RNA secondary structures in the human genome". PLOS Computational Biology. 2 (4): e33. Bibcode:2006PLSCB...2...33P. doi: 10.1371/journal.pcbi.0020033 . PMC   1440920 . PMID   16628248.
147. Coventry A, Kleitman DJ, Berger B (August 2004). "MSARI: multiple sequence alignments for statistical detection of RNA secondary structure". Proceedings of the National Academy of Sciences of the United States of America. 101 (33): 12102–12107. Bibcode:2004PNAS..10112102C. doi: 10.1073/pnas.0404193101 . PMC   514400 . PMID   15304649.
148. Rivas E, Eddy SR (2001). "Noncoding RNA gene detection using comparative sequence analysis". BMC Bioinformatics. 2 (1): 8. doi: 10.1186/1471-2105-2-8 . PMC   64605 . PMID   11801179.
149. Rivas E, Klein RJ, Jones TA, Eddy SR (September 2001). "Computational identification of noncoding RNAs in E. coli by comparative genomics". Current Biology. 11 (17): 1369–1373. Bibcode:2001CBio...11.1369R. doi: 10.1016/S0960-9822(01)00401-8 . PMID   11553332.
150. Washietl S, Hofacker IL, Stadler PF (February 2005). "Fast and reliable prediction of noncoding RNAs". Proceedings of the National Academy of Sciences of the United States of America. 102 (7): 2454–2459. Bibcode:2005PNAS..102.2454W. doi: 10.1073/pnas.0409169102 . PMC   548974 . PMID   15665081.
151. Gruber AR, Neuböck R, Hofacker IL, Washietl S (July 2007). "The RNAz web server: prediction of thermodynamically stable and evolutionarily conserved RNA structures". Nucleic Acids Research. 35 (Web Server issue): W335–W338. doi:10.1093/nar/gkm222. PMC   1933143 . PMID   17452347.
152. Washietl S (2007). "Prediction of Structural Noncoding RNAs with RNAz". Comparative Genomics. Methods in Molecular Biology. Vol. 395. pp. 503–26. doi:10.1007/978-1-59745-514-5_32. ISBN   978-1-58829-693-1. PMID   17993695.
153. Andrews RJ, Roche J, Moss WN (2018). "ScanFold: an approach for genome-wide discovery of local RNA structural elements-applications to Zika virus and HIV". PeerJ. 6: e6136. doi: 10.7717/peerj.6136 . PMC   6317755 . PMID   30627482.
154. Laslett D, Canback B (2004). "ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences". Nucleic Acids Research. 32 (1): 11–16. doi:10.1093/nar/gkh152. PMC   373265 . PMID   14704338.
155. Jha A, Shankar R (2013). "miReader: Discovering Novel miRNAs in Species without Sequenced Genome". PLOS ONE. 8 (6): e66857. Bibcode:2013PLoSO...866857J. doi: 10.1371/journal.pone.0066857 . PMC   3689854 . PMID   23805282.
156. Artzi S, Kiezun A, Shomron N (January 2008). "miRNAminer: a tool for homologous microRNA gene search". BMC Bioinformatics. 9 (1): 39. doi: 10.1186/1471-2105-9-39 . PMC   2258288 . PMID   18215311.
157. Ahmed F, Ansari HR, Raghava GP (April 2009). "Prediction of guide strand of microRNAs from its sequence and secondary structure". BMC Bioinformatics. 10 (1): 105. doi: 10.1186/1471-2105-10-105 . PMC   2676257 . PMID   19358699.
158. Hertel J, Stadler PF (July 2006). "Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data". Bioinformatics. 22 (14): e197–e202. doi: 10.1093/bioinformatics/btl257 . PMID   16873472.
159. Wuyts J, Perrière G, Van De Peer Y (January 2004). "The European ribosomal RNA database". Nucleic Acids Research. 32 (Database issue): D101–D103. doi:10.1093/nar/gkh065. PMC   308799 . PMID   14681368.
160. Szymanski M, Barciszewska MZ, Erdmann VA, Barciszewski J (January 2002). "5S Ribosomal RNA Database". Nucleic Acids Research. 30 (1): 176–178. doi:10.1093/nar/30.1.176. PMC   99124 . PMID   11752286.
161. Lagesen K, Hallin P, Rødland EA, Staerfeldt HH, Rognes T, Ussery DW (2007). "RNAmmer: consistent and rapid annotation of ribosomal RNA genes". Nucleic Acids Research. 35 (9): 3100–3108. doi:10.1093/nar/gkm160. PMC   1888812 . PMID   17452365.
162. Hertel J, Hofacker IL, Stadler PF (January 2008). "SnoReport: computational identification of snoRNAs with unknown targets". Bioinformatics. 24 (2): 158–164. doi: 10.1093/bioinformatics/btm464 . PMID   17895272.
163. Lowe TM, Eddy SR (February 1999). "A computational screen for methylation guide snoRNAs in yeast". Science. 283 (5405): 1168–1171. Bibcode:1999Sci...283.1168L. doi:10.1126/science.283.5405.1168. PMID   10024243.
164. Schattner P, Brooks AN, Lowe TM (July 2005). "The tRNAscan-SE, snoscan and snoGPS web servers for the detection of tRNAs and snoRNAs". Nucleic Acids Research. 33 (Web Server issue): W686–W689. doi:10.1093/nar/gki366. PMC   1160127 . PMID   15980563.
165. Lowe TM, Eddy SR (March 1997). "tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence". Nucleic Acids Research. 25 (5): 955–964. doi:10.1093/nar/25.5.955. PMC   146525 . PMID   9023104.
166. Tempel S, Tahi F (June 2012). "A fast ab-initio method for predicting miRNA precursors in genomes". Nucleic Acids Research. 40 (11): e80. doi:10.1093/nar/gks146. PMC   3367186 . PMID   22362754.
167. Wright ES (October 2021). "FindNonCoding: rapid and simple detection of non-coding RNAs in genomes". Bioinformatics. Oct12 (3): 841–843. doi:10.1093/bioinformatics/btab708. PMC   10060727 . PMID   34636849.
168. Gautheret D, Lambert A (November 2001). "Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles". Journal of Molecular Biology. 313 (5): 1003–1011. doi:10.1006/jmbi.2001.5102. PMID   11700055.
169. Lambert A, Fontaine JF, Legendre M, Leclerc F, Permal E, Major F, et al. (July 2004). "The ERPIN server: an interface to profile-based RNA motif identification". Nucleic Acids Research. 32 (Web Server issue): W160–W165. doi:10.1093/nar/gkh418. PMC   441556 . PMID   15215371.
170. Lambert A, Legendre M, Fontaine JF, Gautheret D (May 2005). "Computing expectation values for RNA motifs using discrete convolutions". BMC Bioinformatics. 6 (1): 118. doi: 10.1186/1471-2105-6-118 . PMC   1168889 . PMID   15892887.
171. Nawrocki EP, Eddy SR (March 2007). "Query-dependent banding (QDB) for faster RNA similarity searches". PLOS Computational Biology. 3 (3): e56. Bibcode:2007PLSCB...3...56N. doi: 10.1371/journal.pcbi.0030056 . PMC   1847999 . PMID   17397253.
172. Eddy SR (July 2002). "A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure". BMC Bioinformatics. 3 (1): 18. doi: 10.1186/1471-2105-3-18 . PMC   119854 . PMID   12095421.
173. Eddy SR, Durbin R (June 1994). "RNA sequence analysis using covariance models". Nucleic Acids Research. 22 (11): 2079–2088. doi:10.1093/nar/22.11.2079. PMC   308124 . PMID   8029015.
174. Sato K, Sakakibara Y (September 2005). "RNA secondary structural alignment with conditional random fields". Bioinformatics. 21. 21 (suppl_2): ii237–ii242. doi: 10.1093/bioinformatics/bti1139 . PMID   16204111.
175. Weinberg Z, Ruzzo WL (August 2004). "Exploiting conserved structure for faster annotation of non-coding RNAs without loss of accuracy". Bioinformatics. 20. 20 (suppl_1): i334–i341. doi: 10.1093/bioinformatics/bth925 . PMID   15262817.
176. Weinberg Z, Ruzzo WL (January 2006). "Sequence-based heuristics for faster annotation of non-coding RNA families". Bioinformatics. 22 (1): 35–39. doi: 10.1093/bioinformatics/bti743 . PMID   16267089.
177. Klein RJ, Eddy SR (September 2003). "RSEARCH: finding homologs of single structured RNA sequences". BMC Bioinformatics. 4 (1): 44. doi: 10.1186/1471-2105-4-44 . PMC   239859 . PMID   14499004.
178. Meyer F, Kurtz S, Backofen R, Will S, Beckstette M (May 2011). "Structator: fast index-based search for RNA sequence-structure patterns". BMC Bioinformatics. 12 (1): 214. doi: 10.1186/1471-2105-12-214 . PMC   3154205 . PMID   21619640.
179. Meyer F, Kurtz S, Beckstette M (July 2013). "Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns". BMC Bioinformatics. 14 (1): 226. doi: 10.1186/1471-2105-14-226 . PMC   3765529 . PMID   23865810.
180. Gardner PP, Giegerich R (September 2004). "A comprehensive comparison of comparative RNA structure prediction approaches". BMC Bioinformatics. 5 (1): 140. doi: 10.1186/1471-2105-5-140 . PMC   526219 . PMID   15458580.
181. Gardner PP, Wilm A, Washietl S (2005). "A benchmark of multiple sequence alignment programs upon structural RNAs". Nucleic Acids Research. 33 (8): 2433–2439. doi:10.1093/nar/gki541. PMC   1087786 . PMID   15860779.
182. Wilm A, Mainz I, Steger G (October 2006). "An enhanced RNA alignment benchmark for sequence alignment programs". Algorithms for Molecular Biology. 1 (1): 19. doi: 10.1186/1748-7188-1-19 . PMC   1635699 . PMID   17062125.
183. Freyhult EK, Bollback JP, Gardner PP (January 2007). "Exploring genomic dark matter: a critical assessment of the performance of homology search methods on noncoding RNA". Genome Research. 17 (1): 117–125. doi:10.1101/gr.5890907. PMC   1716261 . PMID   17151342.
184. Puton T, Kozlowski LP, Rother KM, Bujnicki JM (April 2013). "CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction". Nucleic Acids Research. 41 (7): 4307–4323. doi:10.1093/nar/gkt101. PMC   3627593 . PMID   23435231.
185. Wright ES (May 2020). "RNAconTest: comparing tools for noncoding RNA multiple sequence alignment based on structural consistency". RNA. 26 (5): 531–540. doi:10.1261/rna.073015.119. PMC   7161358 . PMID   32005745.
186. Seibel PN, Müller T, Dandekar T, Schultz J, Wolf M (November 2006). "4SALE--a tool for synchronous RNA sequence and secondary structure alignment and editing". BMC Bioinformatics. 7 (1): 498. doi: 10.1186/1471-2105-7-498 . PMC   1637121 . PMID   17101042.
187. Bendaña YR, Holmes IH (February 2008). "Colorstock, SScolor, Ratón: RNA alignment visualization tools". Bioinformatics. 24 (4): 579–580. doi: 10.1093/bioinformatics/btm635 . PMC   7109877 . PMID   18218657.
188. Nicol JW, Helt GA, Blanchard SG, Raja A, Loraine AE (October 2009). "The Integrated Genome Browser: free software for distribution and exploration of genome-scale datasets". Bioinformatics. 25 (20): 2730–2731. doi:10.1093/bioinformatics/btp472. PMC   2759552 . PMID   19654113.
189. Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ (May 2009). "Jalview Version 2--a multiple sequence alignment editor and analysis workbench". Bioinformatics. 25 (9): 1189–1191. doi:10.1093/bioinformatics/btp033. PMC   2672624 . PMID   19151095.
190. Clamp M, Cuff J, Searle SM, Barton GJ (February 2004). "The Jalview Java alignment editor". Bioinformatics. 20 (3): 426–427. doi: 10.1093/bioinformatics/btg430 . PMID   14960472.
191. Griffiths-Jones S (January 2005). "RALEE--RNA ALignment editor in Emacs". Bioinformatics. 21 (2): 257–259. doi: 10.1093/bioinformatics/bth489 . PMID   15377506.
192. Andersen ES, Lind-Thomsen A, Knudsen B, Kristensen SE, Havgaard JH, Torarinsson E, et al. (November 2007). "Semiautomated improvement of RNA alignments". RNA. 13 (11): 1850–1859. doi:10.1261/rna.215407. PMC   2040093 . PMID   17804647.
193. Lee J, Kladwang W, Lee M, Cantu D, Azizyan M, Kim H, et al. (February 2014). "RNA design rules from a massive open laboratory". Proceedings of the National Academy of Sciences of the United States of America. 111 (6): 2122–2127. Bibcode:2014PNAS..111.2122L. doi: 10.1073/pnas.1313039111 . PMC   3926058 . PMID   24469816.
194. Garcia-Martin JA, Clote P, Dotu I (April 2013). "RNAiFOLD: a constraint programming algorithm for RNA inverse folding and molecular design". Journal of Bioinformatics and Computational Biology. 11 (2): 1350001. doi:10.1142/S0219720013500017. PMID   23600819.
195. Garcia-Martin JA, Clote P, Dotu I (July 2013). "RNAiFold: a web server for RNA inverse folding and molecular design". Nucleic Acids Research. 41 (Web Server issue): W465–W470. doi:10.1093/nar/gkt280. PMC   3692061 . PMID   23700314.
196. Garcia-Martin JA, Dotu I, Clote P (July 2015). "RNAiFold 2.0: a web server and software to design custom and Rfam-based RNA molecules". Nucleic Acids Research. 43 (W1): W513–W521. arXiv: 1505.04210 . Bibcode:2015arXiv150504210G. doi:10.1093/nar/gkv460. PMC   4489274 . PMID   26019176.
197. Andronescu M, Fejes AP, Hutter F, Hoos HH, Condon A (February 2004). "A new algorithm for RNA secondary structure design". Journal of Molecular Biology. 336 (3): 607–624. doi:10.1016/j.jmb.2003.12.041. PMID   15095976.
198. Busch A, Backofen R (August 2006). "INFO-RNA--a fast approach to inverse RNA folding". Bioinformatics. 22 (15): 1823–1831. doi: 10.1093/bioinformatics/btl194 . PMID   16709587.
199. Busch A, Backofen R (July 2007). "INFO-RNA--a server for fast inverse RNA folding satisfying sequence constraints". Nucleic Acids Research. 35 (Web Server issue): W310–W313. doi:10.1093/nar/gkm218. PMC   1933236 . PMID   17452349.
200. Avihoo A, Churkin A, Barash D (August 2011). "RNAexinv: An extended inverse RNA folding from shape and physical attributes to sequences". BMC Bioinformatics. 12 (319): 319. doi: 10.1186/1471-2105-12-319 . PMC   3176266 . PMID   21813013.
201. Levin A, Lis M, Ponty Y, O'Donnell CW, Devadas S, Berger B, Waldispühl J (November 2012). "A global sampling approach to designing and reengineering RNA secondary structures". Nucleic Acids Research. 40 (20): 10041–10052. doi:10.1093/nar/gks768. PMC   3488226 . PMID   22941632.
202. Reinharz V, Ponty Y, Waldispühl J (July 2013). "A weighted sampling algorithm for the design of RNA sequences with targeted secondary structure and nucleotide distribution". Bioinformatics. 29 (13): i308–i315. doi:10.1093/bioinformatics/btt217. PMC   3694657 . PMID   23812999.
203. Matthies MC, Bienert S, Torda AE (October 2012). "Dynamics in Sequence Space for RNA Secondary Structure Design". Journal of Chemical Theory and Computation. 8 (10): 3663–3670. doi:10.1021/ct300267j. PMID   26593011.
204. Taneda A (2011). "MODENA: a multi-objective RNA inverse folding". Advances and Applications in Bioinformatics and Chemistry. 4: 1–12. doi: 10.2147/aabc.s14335 . PMC   3169953 . PMID   21918633.
205. Taneda A (2012). "Multi-objective genetic algorithm for pseudoknotted RNA sequence design". Frontiers in Genetics. 3: 36. doi: 10.3389/fgene.2012.00036 . PMC   3337422 . PMID   22558001.
206. Esmaili-Taheri A, Ganjtabesh M, Mohammad-Noori M (May 2014). "Evolutionary solution for the RNA design problem". Bioinformatics. 30 (9): 1250–1258. doi: 10.1093/bioinformatics/btu001 . PMID   24407223.
207. Kleinkauf R, Mann M, Backofen R (October 2015). "antaRNA: ant colony-based RNA sequence design". Bioinformatics. 31 (19): 3114–3121. doi:10.1093/bioinformatics/btv319. PMC   4576691 . PMID   26023105.
208. Kleinkauf R, Houwaart T, Backofen R, Mann M (November 2015). "antaRNA--Multi-objective inverse folding of pseudoknot RNA using ant-colony optimization". BMC Bioinformatics. 16 (389): 389. doi: 10.1186/s12859-015-0815-6 . PMC   4652366 . PMID   26581440.
209. Flamm C, Hofacker IL, Maurer-Stroh S, Stadler PF, Zehl M (February 2001). "Design of multistable RNA molecules". RNA. 7 (2): 254–265. doi:10.1017/s1355838201000863. PMC   1370083 . PMID   11233982.
210. Rodrigo G, Jaramillo A (September 2014). "RiboMaker: computational design of conformation-based riboregulation". Bioinformatics. 30 (17): 2508–2510. doi: 10.1093/bioinformatics/btu335 . PMID   24833802.
211. Hammer S, Tschiatschek B, Flamm C, Hofacker IL, Findeiß S (September 2017). "RNAblueprint: flexible multiple target nucleic acid sequence design". Bioinformatics. 33 (18): 2850–2858. doi:10.1093/bioinformatics/btx263. PMC   5870862 . PMID   28449031.
212. Höner zu Siederdissen C, Hammer S, Abfalter I, Hofacker IL, Flamm C, Stadler PF (December 2013). "Computational design of RNAs with complex energy landscapes". Biopolymers. 99 (12): 1124–1136. doi:10.1002/bip.22337. PMID   23818234. S2CID   7337968.
213. Lyngsø RB, Anderson JW, Sizikova E, Badugu A, Hyland T, Hein J (October 2012). "Frnakenstein: multiple target inverse RNA folding". BMC Bioinformatics. 13 (260): 260. doi: 10.1186/1471-2105-13-260 . PMC   3534541 . PMID   23043260.
214. Shu W, Liu M, Chen H, Bo X, Wang S (December 2010). "ARDesigner: a web-based system for allosteric RNA design". Journal of Biotechnology. 150 (4): 466–473. doi:10.1016/j.jbiotec.2010.10.067. PMID   20969900.
215. Byun Y, Han K (June 2009). "PseudoViewer3: generating planar drawings of large-scale RNA structures with pseudoknots". Bioinformatics. 25 (11): 1435–1437. doi: 10.1093/bioinformatics/btp252 . PMID   19369500.
216. Byun Y, Han K (July 2006). "PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structures". Nucleic Acids Research. 34 (Web Server issue): W416–W422. doi:10.1093/nar/gkl210. PMC   1538805 . PMID   16845039.
217. Han K, Byun Y (July 2003). "PSEUDOVIEWER2: Visualization of RNA pseudoknots of any type". Nucleic Acids Research. 31 (13): 3432–3440. doi:10.1093/nar/gkg539. PMC   168946 . PMID   12824341.
218. Han K, Lee Y, Kim W (2002). "PseudoViewer: automatic visualization of RNA pseudoknots". Bioinformatics. 18. 18 (Suppl 1): S321–S328. doi: 10.1093/bioinformatics/18.suppl_1.S321 . PMID   12169562.
219. Kaiser A, Krüger J, Evers DJ (July 2007). "RNA Movies 2: sequential animation of RNA secondary structures". Nucleic Acids Research. 35 (Web Server issue): W330–W334. doi:10.1093/nar/gkm309. PMC   1933240 . PMID   17567618.
220. Evers D, Giegerich R (January 1999). "RNA movies: visualizing RNA secondary structure spaces". Bioinformatics. 15 (1): 32–37. doi: 10.1093/bioinformatics/15.1.32 . PMID   10068690.
221. Tsang HH, Dai DC (2012). "RNA-DV". Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine. pp. 601–603. doi:10.1145/2382936.2383036. ISBN   978-1-4503-1670-5. S2CID   15910737.
222. Martinez HM, Maizel JV, Shapiro BA (June 2008). "RNA2D3D: a program for generating, viewing, and comparing 3-dimensional models of RNA". Journal of Biomolecular Structure & Dynamics. 25 (6): 669–683. doi:10.1080/07391102.2008.10531240. PMC   3727907 . PMID   18399701.
223. Reuter JS, Mathews DH (March 2010). "RNAstructure: software for RNA secondary structure prediction and analysis". BMC Bioinformatics. 11 (1): 129. doi: 10.1186/1471-2105-11-129 . PMC   2984261 . PMID   20230624.
224. Yang H, Jossinet F, Leontis N, Chen L, Westbrook J, Berman H, Westhof E (July 2003). "Tools for the automatic identification and classification of RNA base pairs". Nucleic Acids Research. 31 (13): 3450–3460. doi:10.1093/nar/gkg529. PMC   168936 . PMID   12824344.
225. Menzel P, Seemann SE, Gorodkin J (October 2012). "RILogo: visualizing RNA-RNA interactions". Bioinformatics. 28 (19): 2523–2526. doi: 10.1093/bioinformatics/bts461 . PMID   22826541.
226. Darty K, Denise A, Ponty Y (August 2009). "VARNA: Interactive drawing and editing of the RNA secondary structure". Bioinformatics. 25 (15): 1974–1975. doi:10.1093/bioinformatics/btp250. PMC   2712331 . PMID   19398448.
227. Kerpedjiev P, Hammer S, Hofacker IL (October 2015). "Forna (force-directed RNA): Simple and effective online RNA secondary structure diagrams". Bioinformatics. 31 (20): 3377–3379. doi:10.1093/bioinformatics/btv372. PMC   4595900 . PMID   26099263.
228. Weinberg Z, Breaker RR (January 2011). "R2R--software to speed the depiction of aesthetic consensus RNA secondary structures". BMC Bioinformatics. 12 (1): 3. doi: 10.1186/1471-2105-12-3 . PMC   3023696 . PMID   21205310.
229. Johnson PZ, Simon AE (July 2023). "RNAcanvas: interactive drawing and exploration of nucleic acid structures". Nucleic Acids Research. 51 (w1): W501–W508. doi:10.1093/nar/gkad302. PMC   10320051 . PMID   37094080.
230. Mitra, Raktim; Cohen, Ari S; Rohs, Remo (2024-04-17). "RNAscape: geometric mapping and customizable visualization of RNA structure". Nucleic Acids Research. doi: 10.1093/nar/gkae269 . ISSN   0305-1048.