List of RNA structure prediction software explained

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 ^[1]	no>.	Links	References
SQUARNA	Secondary structure prediction based on a greedy stem formation model		sourcecode	^[2]
CentroidFold	Secondary structure prediction based on generalized centroid estimator		sourcecode webserver	^[3]
CentroidHomfold	Secondary structure prediction by using homologous sequence information		sourcecode webserver	^[4]
Context Fold	An RNA secondary structure prediction software based on feature-rich trained scoring models.		sourcecode webserver	^[5]
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.		sourcecode webserver	^[6]
Crumple	Simple, cleanly written software to produce the full set of possible secondary structures for one sequence, given optional constraints.		sourcecode	^[7]
CyloFold	Secondary structure prediction method based on placement of helices allowing complex pseudoknots.		webserver	^[8]
E2Efold	A deep learning based method for efficiently predicting secondary structure by differentiating through a constrained optimization solver, without using dynamic programming.		sourcecode	^[9] ^[10]
EternaFold	A multitask-learning-based model trained on data from the Eterna project.		sourcecode webserver	^[11]
GTFold	Fast and scalable multicore code for predicting RNA secondary structure.		link sourcecode	^[12]
INTERPIN	Algorithm and database for prediction of transcription termination sites in bacteria. Uses Mfold for RNA secondary structure prediction.		webserver	^[13] ^[14]
IPknot	Fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming.		sourcecode webserver	^[15]
KineFold	Folding kinetics of RNA sequences including pseudoknots by including an implementation of the partition function for knots.		linuxbinary, webserver	^[16] ^[17]
Mfold	MFE (Minimum Free Energy) RNA structure prediction algorithm.		sourcecode, webserver	^[18]
pKiss	A dynamic programming algorithm for the prediction of a restricted class (H-type and kissing hairpins) of RNA pseudoknots.		sourcecode, webserver	^[19]
Pknots	A dynamic programming algorithm for optimal RNA pseudoknot prediction using the nearest neighbour energy model.		sourcecode	^[20]
PknotsRG	A dynamic programming algorithm for the prediction of a restricted class (H-type) of RNA pseudoknots.		sourcecode, webserver	^[21]
RNA123	Secondary structure prediction via thermodynamic-based folding algorithms and novel structure-based sequence alignment specific for RNA.		webserver
	MFE RNA structure prediction algorithm. Includes an implementation of the partition function for computing basepair probabilities and circular RNA folding.		sourcecode, webserver	^[22] ^[23] ^[24] ^[25]
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.		source & binaries, webserver	^[26] ^[27]
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.		source & binaries, webserver	^[28] ^[29]
SARNA-Predict	RNA Secondary structure prediction method based on simulated annealing. It can also predict structure with pseudoknots.		link	^[30]
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.		link & source
Sfold	Statistical sampling of all possible structures. The sampling is weighted by partition function probabilities.		Github_Repository	^[31] ^[32] ^[33] ^[34]
Sliding Windows & Assembly	Sliding windows and assembly is a tool chain for folding long series of similar hairpins.		sourcecode
SPOT-RNA	SPOT-RNA is first RNA secondary structure predictor which can predict all kind base pairs (canonical, noncanonical, pseudoknots, and base triplets).		sourcecodewebserver	^[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.		sourcecode	^[36]
UFold	UFold: fast and accurate RNA secondary structure prediction with deep learning		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.		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.		webserver	^[39] ^[40]
Notes:

Single sequence tertiary structure prediction

Name	Description	Knots ^[41]	no>.	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.		webserver sourcecode	^[42]
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.		sourcecode	^[43]
FARFAR2	Automated de novo prediction of native-like RNA tertiary structures .		webserver	^[44]
iFoldRNA	three-dimensional RNA structure prediction and folding		webserver	^[45]
MC-Fold MC-Sym Pipeline	Thermodynamics and Nucleotide cyclic motifs for RNA structure prediction algorithm. 2D and 3D structures.		sourcecode, webserver	^[46]
NAST	Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters		executables	^[47]
MMB	Turning limited experimental information into 3D models of RNA		sourcecode	^[48]
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.
RNAComposer	Fully automated prediction of large RNA 3D structures.		webserver webserver	^[49]
Notes:

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 ^[50]	num>.	Alignment ^[51]	yes	no>.	Structure ^[52]	yes	no>.	Knots ^[53]	no>.	Link	References
SQUARNA	Common secondary structure prediction based on a greedy stem formation model					sourcecode	^[54]
Carnac	Comparative analysis combined with MFE folding.					sourcecode, webserver	^[55] ^[56]
CentroidAlifold	Common secondary structure prediction based on generalized centroid estimator					sourcecode	^[57]
CentroidAlign	Fast and accurate multiple aligner for RNA sequences					sourcecode	^[58]
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.					sourcecode, webserver, website	^[59]
CONSAN	implements a pinned Sankoff algorithm for simultaneous pairwise RNA alignment and consensus structure prediction.					sourcecode	^[60]
DAFS	Simultaneous aligning and folding of RNA sequences via dual decomposition.					sourcecode	^[61]
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.					sourcecode	^[62] ^[63] ^[64]
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.					sourcecode, webserver, website	^[65]
FoldalignM	A multiple RNA structural RNA alignment method, to a large extent based on the PMcomp program.					sourcecode	^[66]
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.					sourcecode, webserver	^[67] ^[68]
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.					sourcecode	^[69]
KNetFold	Computes a consensus RNA secondary structure from an RNA sequence alignment based on machine learning.					linuxbinary, webserver	^[70]
LARA	Produce a global fold and alignment of ncRNA families using integer linear programming and Lagrangian relaxation.					sourcecode	^[71]
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.					sourcecode, webserver	^[72]
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.					sourcecode	^[73] ^[74]
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.					sourcecode	^[75]
Murlet	a multiple alignment tool for RNA sequences using iterative alignment based on Sankoff's algorithm with sharply reduced computational time and memory.					webserver	^[76]
MXSCARNA	a multiple alignment tool for RNA sequences using progressive alignment based on pairwise structural alignment algorithm of SCARNA.					webserver sourcecode	^[77]
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.					webserver sourcecode
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.					sourcecode	^[78]
Pfold	Folds alignments using a SCFG trained on rRNA alignments.					webserver	^[79] ^[80]
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.					sourcecode	^[81]
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.					sourcecode	^[82]
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					sourcecode, webserver	^[83]
RNAG	A Gibbs sampling method to determine a conserved structure and the structural alignment.					sourcecode	^[84]
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.					sourcecode, webserver	^[85] ^[86]
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					sourcecode	^[87] ^[88]
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.					home page	^[89]
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.					webserver
RNAalifold	Folds precomputed alignments using mix of free-energy and covariation measures. Ships with the ViennaRNA Package.					homepage	^[90]
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.					sourcecode, webserver	^[91]
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.					sourcecode, webserver	^[92]
RNAforester	Compare and align RNA secondary structures via a "forest alignment" approach.					sourcecode, webserver	^[93] ^[94]
RNAmine	Frequent stem pattern miner from unaligned RNA sequences is a software tool to extract the structural motifs from a set of RNA sequences.					webserver	^[95]
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.					sourcecode	^[96]
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.					webserver	^[97]
SimulFold	simultaneously inferring RNA structures including pseudoknots, alignments, and trees using a Bayesian MCMC framework.					sourcecode	^[98]
Stemloc	a program for pairwise RNA structural alignment based on probabilistic models of RNA structure known as Pair stochastic context-free grammars.					sourcecode	^[99]
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.					sourcecode, webserver	^[100]
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.					webserver	^[101]
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.					webserver	^[102]
Xrate	a program for analysis of multiple sequence alignments using phylogenetic grammars, that may be viewed as a flexible generalization of the "Pfold" program.					sourcecode	^[103]
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	sourcecodesourcecode webserver	^[104] ^[105]
Notes:

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	^[106]
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.	sourcecodewebserver	^[107]
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	^[108]

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			sourcecode	^[109]
RNApredator	RNApredator uses a dynamic programming approach to compute RNA-RNA interaction sites.			webserver	^[110]
GUUGle	A utility for fast determination of RNA-RNA matches with perfect hybridization via A-U, C-G, and G-U base pairing.			webserver	^[111]
IntaRNA	Efficient target prediction incorporating the accessibility of target sites.			sourcecode webserver	^[112] ^[113] ^[114] ^[115] ^[116]
CopraRNA	Tool for sRNA target prediction. It computes whole genome predictions by mix of distinct whole genome IntaRNA predictions.			sourcecode webserver	^[117] ^[118]
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.			sourcecode webserver	^[119]
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.			NUPACK	^[120]
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.			http://rna.urmc.rochester.edu	^[121]
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.			linuxbinary	^[122]
piRNAPred	an integrated framework for piRNA prediction employing hybrid features like k-mer nucleotide composition, secondary structure, thermodynamic and physicochemical properties.			https://github.com/IshaMonga/piRNAPred	^[123]
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.			http://www.bioinf.uni-leipzig.de/~qin/resources/ripalign.tar.gz	^[124]
RactIP	Fast and accurate prediction of RNA-RNA interaction using integer programming.			sourcecode webserver	^[125]
RNAaliduplex	Based on RNAduplex with bonuses for covarying sites			sourcecode
RNAcofold	Works much like RNAfold, but allows specifying two RNA sequences which are then allowed to form a dimer structure.			sourcecode	^[126]
RNAduplex	Computes optimal and suboptimal secondary structures for hybridization. The calculation is simplified by allowing only inter-molecular base pairs.			sourcecode
RNAhybrid	Tool to find the minimum free energy hybridisation of a long and a short RNA (≤ 30 nt).			sourcecode, webserver	^[127] ^[128]
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.			sourcecode	^[129]

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.				Web tool	^[130]
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.				precomputed predictions interactive/custom sequences	^[131]
RNAhybrid	Tool to find the minimum free energy hybridisation of a long and a short RNA (≤ 30 nt).				sourcecode, webserver
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.				sourcecode, webserver	^[132]

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),^[133] (Alexiou et al., Bioinformatics 2009),^[134] or (Ritchie et al., Nature Methods 2009)^[135]

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.				software (MATLAB)	^[136]
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.				webserver	^[137]
MicroTar	An animal miRNA target prediction tool based on miRNA-target complementarity and thermodynamic data.				sourcecode	^[138]
miTarget	microRNA target gene prediction using a support vector machine.				webserver	^[139]
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				webserver	^[140] ^[141]
PicTar	Combinatorial microRNA target predictions.				predictions	^[142]
PITA	Incorporates the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition.				executable, webserver, predictions	^[143]
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.				precomputed predictions interactive/custom sequences	^[144]
RNAhybrid	Tool to find the minimum free energy hybridisation of a long and a short RNA (≤ 30 nt).				sourcecode, webserver
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.				sourcecode webserver	^[145] ^[146]
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.				server/sourcecode	^[147]
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.				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.				sourcecode, webserver	^[148] ^[149] ^[150] ^[151] ^[152] ^[153]

ncRNA gene prediction software

Name	Description	Number of sequences ^[154]	num>.	Alignment ^[155]	yes	no>.	Structure ^[156]	yes	no>.	Link	References
Alifoldz	Assessing a multiple sequence alignment for the existence of an unusual stable and conserved RNA secondary structure.				sourcecode	^[157]
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.				linuxbinary	^[158]
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	^[159]
MSARi	heuristic search for statistically significant conservation of RNA secondary structure in deep multiple sequence alignments.				sourcecode	^[160]
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.				sourcecode	^[161] ^[162]
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.				sourcecode, webserver RNAz 2	^[163] ^[164] ^[165]
ScanFold	A program for predicting unique local RNA structures in large sequences with unusually stable folding.				sourcecode webserver	^[166]
Xrate	a program for analysis of multiple sequence alignments using phylogenetic grammars, that may be viewed as a flexible generalization of the "Evofold" program.				sourcecode
Notes:

Family specific gene prediction software

Name	Description	Family	Link	References
ARAGORN	ARAGORN detects tRNA and tmRNA in nucleotide sequences.		webserver source	^[167]
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	^[168]
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.		webserver	^[169]
RISCbinder	Prediction of guide strand of microRNAs.		webserver	^[170]
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.		homepage	^[171]
RNAmmer	RNAmmer uses HMMER to annotate rRNA genes in genome sequences. Profiles were built using alignments from the European ribosomal RNA database^[172] and the 5S Ribosomal RNA Database.^[173]		webserver source	^[174]
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.		sourcecode	^[175]
SnoScan	Search for C/D box methylation guide snoRNA genes in a genomic sequence.		sourcecode, webserver	^[176] ^[177]
tRNAscan-SE	a program for the detection of transfer RNA genes in genomic sequence.		sourcecode, webserver	^[178]
miRNAFold	A fast ab initio software for searching for microRNA precursors in genomes.		webserver	^[179]

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	^[180]
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	^[181] ^[182] ^[183]
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	^[184] ^[185] ^[186]
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	^[187]
PHMMTS	"pair hidden Markov models on tree structures" is an extension of pair hidden Markov models defined on alignments of trees.	sourcecode, webserver	^[188]
RaveNnA	A slow and rigorous or fast and heuristic sequence-based filter for covariance models.	sourcecode	^[189] ^[190]
RSEARCH	Takes one RNA sequence with its secondary structure and uses a local alignment algorithm to search a database for homologous RNAs.	[ftp://selab.janelia.org/pub/software/rsearch/ sourcecode]	^[191]
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	^[192]
RaligNAtor	Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns	sourcecode	^[193]

Benchmarks

Name	Description	Structure^[194]	no>.	Alignment^[195]	no>.	Phylogeny	Links	References
BRalibase I	A comprehensive comparison of comparative RNA structure prediction approaches				data	^[196]
BRalibase II	A benchmark of multiple sequence alignment programs upon structural RNAs				data	^[197]
BRalibase 2.1	A benchmark of multiple sequence alignment programs upon structural RNAs				data	^[198]
BRalibase III	A critical assessment of the performance of homology search methods on noncoding RNA				data	^[199]
CompaRNA	An independent comparison of single-sequence and comparative methods for RNA secondary structure prediction				AMU mirror or IIMCB mirror	^[200]
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				data	^[201]
Notes:

Alignment viewers, editors

Name	Description	Alignment^[202]	no>.	Structure^[203]	no>.	Link	References
4sale	A tool for Synchronous RNA Sequence and Secondary Structure Alignment and Editing			sourcecode	^[204]
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.			sourcecode	^[205]
Integrated Genome Browser (IGB)	Multiple alignment viewer written in Java.			sourcecode	^[206]
Jalview	Multiple alignment editor written in Java.			sourcecode	^[207] ^[208]
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.			sourcecode	^[209]
SARSE	A graphical sequence editor for working with structural alignments of RNA.			sourcecode	^[210]
Notes:

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	^[211]
RNAinverse	The ViennaRNA Package provides RNAinverse, an algorithm for designing sequences with desired structure.	Web Server
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	^[212] ^[213] ^[214]
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	^[215]
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	^[216] ^[217]
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	^[218]
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	^[219]
IncaRNAtion		Source Code	^[220]
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	^[221]
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	^[222] ^[223]
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	^[224]
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	^[225] ^[226]
	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	^[227]
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	^[228]
	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	^[229]
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	^[230]
Frnakenstein	Frnakenstein applies a genetic algorithm to solve the inverse RNA folding problem.	Source Code	^[231]
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.	http://biotech.bmi.ac.cn/ARDesigner	^[232]

Notes:

Secondary structure viewers, editors

Name	Description	Link	References
PseudoViewer	Automatically visualizing RNA pseudoknot structures as planar graphs.	webapp/binary	^[233] ^[234] ^[235] ^[236]
RNA Movies	browse sequential paths through RNA secondary structure landscapes	sourcecode	^[237] ^[238]
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	^[239]
RNA2D3D	Program to generate, view, and compare 3-dimensional models of RNA	binary	^[240]
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	^[241]
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	^[242]
RILogo	Visualizes the intra-/intermolecular base pairing of two interacting RNAs with sequence logos in a planar graph.	web server / sourcecode	^[243]
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	^[244]
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.	webappfornac sourceforna source	^[245]
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	^[246]
RNAcanvas	A web app for drawing and exploring nucleic acid structures.	webapp	^[247]
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.	webserversourcecode	^[248]

See also

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

Notes and References

1. Knots: Pseudoknot prediction,
2. DR Bohdan . GI Nikolaev . JM Bujnicki . EF Baulin . SQUARNA - an RNA secondary structure prediction method based on a greedy stem formation model . August 2023 . 10.1101/2023.08.28.555103 . free .
3. Hamada M, Kiryu H, Sato K, Mituyama T, Asai K . Prediction of RNA secondary structure using generalized centroid estimators . Bioinformatics . 25 . 4 . 465–473 . February 2009 . 19095700 . 10.1093/bioinformatics/btn601 . free .
4. Hamada M, Sato K, Kiryu H, Mituyama T, Asai K . Predictions of RNA secondary structure by combining homologous sequence information . Bioinformatics . 25 . 12 . i330–i338 . June 2009 . 19478007 . 2687982 . 10.1093/bioinformatics/btp228 .
5. Zakov S, Goldberg Y, Elhadad M, Ziv-Ukelson M . Rich parameterization improves RNA structure prediction . Journal of Computational Biology . 18 . 11 . 1525–1542 . November 2011 . 22035327 . 10.1089/cmb.2011.0184 . 2011LNCS.6577..546Z .
6. Do CB, Woods DA, Batzoglou S . CONTRAfold: RNA secondary structure prediction without physics-based models . Bioinformatics . 22 . 14 . e90–e98 . July 2006 . 16873527 . 10.1093/bioinformatics/btl246 . free .
7. Schroeder SJ, Stone JW, Bleckley S, Gibbons T, Mathews DM . Ensemble of secondary structures for encapsidated satellite tobacco mosaic virus RNA consistent with chemical probing and crystallography constraints . Biophysical Journal . 101 . 1 . 167–175 . July 2011 . 21723827 . 3127170 . 10.1016/j.bpj.2011.05.053 . 2011BpJ...101..167S .
8. Bindewald E, Kluth T, Shapiro BA . CyloFold: secondary structure prediction including pseudoknots . Nucleic Acids Research . 38 . Web Server issue . W368–W372 . July 2010 . 20501603 . 2896150 . 10.1093/nar/gkq432 .
9. Chen X, Li Y, Umarov R, Gao X, Song L . RNA Secondary Structure Prediction By Learning Unrolled Algorithms. 2020. 2002.05810. cs.LG.
10. 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.
11. 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 . en . 19 . 10 . 1234–1242 . 10.1038/s41592-022-01605-0 . 36192461 . 9839360 . 1548-7105. free .
12. Swenson MS, Anderson J, Ash A, Gaurav P, Sükösd Z, Bader DA, Harvey SC, Heitsch CE . 6 . GTfold: enabling parallel RNA secondary structure prediction on multi-core desktops . BMC Research Notes . 5 . 341 . July 2012 . 22747589 . 3748833 . 10.1186/1756-0500-5-341 . free .
13. Gupta . Swati . Padmashali . Namrata . Pal . Debnath . November 2023 . INTERPIN: A repository for intrinsic transcription termination hairpins in bacteria . Biochimie . en . 214 . Pt B . 228–236 . 10.1016/j.biochi.2023.07.018. 37499897 .
14. Gupta . Swati . Pal . Debnath . 2021-08-10 . Clusters of hairpins induce intrinsic transcription termination in bacteria . Scientific Reports . en . 11 . 1 . 16194 . 10.1038/s41598-021-95435-3 . 2045-2322 . 8355165 . 34376740. 2021NatSR..1116194G .
15. Sato K, Kato Y, Hamada M, Akutsu T, Asai K . IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming . Bioinformatics . 27 . 13 . i85–i93 . July 2011 . 21685106 . 3117384 . 10.1093/bioinformatics/btr215 .
16. Xayaphoummine A, Bucher T, Isambert H . Kinefold web server for RNA/DNA folding path and structure prediction including pseudoknots and knots . Nucleic Acids Research . 33 . Web Server issue . W605–W610 . July 2005 . 15980546 . 1160208 . 10.1093/nar/gki447 .
17. Xayaphoummine A, Bucher T, Thalmann F, Isambert H . 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 . December 2003 . 14676318 . 307563 . 10.1073/pnas.2536430100 . physics/0309117 . free . 2003PNAS..10015310X .
18. Zuker M, Stiegler P . Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information . Nucleic Acids Research . 9 . 1 . 133–148 . January 1981 . 6163133 . 326673 . 10.1093/nar/9.1.133 .
19. Prediction of RNA Secondary Structure Including Kissing Hairpin Motifs . Theis C, Janssen S, Giegerich R . 2010 . Moulton V, Singh M . 6293 . Lecture Notes in Computer Science . Algorithms in Bioinformatics . Springer Berlin Heidelberg . 978-3-642-15293-1 . 10.1007/978-3-642-15294-8_5 . 52–64. free .
20. Rivas E, Eddy SR . A dynamic programming algorithm for RNA structure prediction including pseudoknots . Journal of Molecular Biology . 285 . 5 . 2053–2068 . February 1999 . 9925784 . 10.1006/jmbi.1998.2436 . physics/9807048 . 2228845 .
21. Reeder J, Steffen P, Giegerich R . pknotsRG: RNA pseudoknot folding including near-optimal structures and sliding windows . Nucleic Acids Research . 35 . Web Server issue . W320–W324 . July 2007 . 17478505 . 1933184 . 10.1093/nar/gkm258 .
22. Hofacker IL, Fontana W, Stadler PF, Bonhoeffer A, Tacker M, Schuster P . Fast Folding and Comparison of RNA Secondary Structures. . Monatshefte für Chemie . 125 . 2 . 167–188 . 1994 . 10.1007/BF00818163. 19344304 .
23. McCaskill JS . The equilibrium partition function and base pair binding probabilities for RNA secondary structure . Biopolymers . 29 . 6–7 . 1105–1119 . 1990 . 1695107 . 10.1002/bip.360290621 . free . 12629688 . 11858/00-001M-0000-0013-0DE3-9 .
24. Hofacker IL, Stadler PF . Memory efficient folding algorithms for circular RNA secondary structures . Bioinformatics . 22 . 10 . 1172–1176 . May 2006 . 16452114 . 10.1093/bioinformatics/btl023 . circular RNA . free .
25. Bompfünewerer AF, Backofen R, Bernhart SH, Hertel J, Hofacker IL, Stadler PF, Will S . Variations on RNA folding and alignment: lessons from Benasque . Journal of Mathematical Biology . 56 . 1–2 . 129–144 . January 2008 . 17611759 . 10.1007/s00285-007-0107-5 . 15637111 . 10.1.1.188.1420 .
26. Giegerich R, Voss B, Rehmsmeier M . Abstract shapes of RNA . Nucleic Acids Research . 32 . 16 . 4843–4851 . 2004 . 15371549 . 519098 . 10.1093/nar/gkh779 .
27. Voss B, Giegerich R, Rehmsmeier M . Complete probabilistic analysis of RNA shapes . BMC Biology . 4 . 1 . 5 . February 2006 . 16480488 . 1479382 . 10.1186/1741-7007-4-5 . free .
28. Mathews DH, Disney MD, Childs JL, Schroeder SJ, Zuker M, Turner DH . 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 . May 2004 . 15123812 . 409911 . 10.1073/pnas.0401799101 . free . 2004PNAS..101.7287M .
29. Mathews DH . Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization . RNA . 10 . 8 . 1178–1190 . August 2004 . 15272118 . 1370608 . 10.1261/rna.7650904 .
30. Tsang HH, Wiese KC . 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 . 2010 . 21030739 . 10.1109/TCBB.2008.97 . 12095376 .
31. Ding Y, Lawrence CE . A statistical sampling algorithm for RNA secondary structure prediction . Nucleic Acids Research . 31 . 24 . 7280–7301 . December 2003 . 14654704 . 297010 . 10.1093/nar/gkg938 .
32. Ding Y, Chan CY, Lawrence CE . Sfold web server for statistical folding and rational design of nucleic acids . Nucleic Acids Research . 32 . Web Server issue . W135–W141 . July 2004 . 15215366 . 441587 . 10.1093/nar/gkh449 .
33. Ding Y, Chan CY, Lawrence CE . RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble . RNA . 11 . 8 . 1157–1166 . August 2005 . 16043502 . 1370799 . 10.1261/rna.2500605 .
34. Chan CY, Lawrence CE, Ding Y . Structure clustering features on the Sfold Web server . Bioinformatics . 21 . 20 . 3926–3928 . October 2005 . 16109749 . 10.1093/bioinformatics/bti632 . free .
35. Singh J, Hanson J, Paliwal K, Zhou Y . RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning . Nature Communications . 10 . 1 . 5407 . November 2019 . 31776342 . 6881452 . 10.1038/s41467-019-13395-9 . 2019NatCo..10.5407S .
36. Barsacchi M, Novoa EM, Kellis M, Bechini A . SwiSpot: modeling riboswitches by spotting out switching sequences . Bioinformatics . 32 . 21 . 3252–3259 . November 2016 . 27378291 . 10.1093/bioinformatics/btw401 . free . 11568/817190 . free .
37. Fu L, Cao Y, Wu J, Peng Q, Nie Q, Xie X . UFold: fast and accurate RNA secondary structure prediction with deep learning . Nucleic Acids Research . 50 . 3 . 14. February 2022 . 34792173 . 10.1093/nar/gkab1074 . 8860580 . free .
38. Book: Markham NR, Zuker M . UNAFold . Bioinformatics . 453 . 3–31 . 2008 . 18712296 . 10.1007/978-1-60327-429-6_1. Methods in Molecular Biology . 978-1-60327-428-9 .
39. Dawson WK, Fujiwara K, Kawai G . Prediction of RNA pseudoknots using heuristic modeling with mapping and sequential folding . PLOS ONE . 2 . 9 . e905 . September 2007 . 17878940 . 1975678 . 10.1371/journal.pone.0000905 . free . 2007PLoSO...2..905D .
40. Dawson WK, Takai T, Ito N, Shimizu K, Kawai G . 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 . 2014 . 10.4081/jnai.2014.2652 . free .
41. Knots: Pseudoknot prediction,
42. Wang W, et al . trRosettaRNA: automated prediction of RNA 3D structure with transformer network . Nature Communications . 14 . 1 . 7266 . Nov 2023 . 37945552 . 10636060. 10.1038/s41467-023-42528-4 . 2023NatCo..14.7266W .
43. Frellsen J, Moltke I, Thiim M, Mardia KV, Ferkinghoff-Borg J, Hamelryck T . A probabilistic model of RNA conformational space . PLOS Computational Biology . 5 . 6 . e1000406 . June 2009 . 19543381 . 2691987 . 10.1371/journal.pcbi.1000406 . 2009PLSCB...5E0406F . free .
44. Watkins . Andrew Martin . Rangan . Ramya . Das . Rhiju . 2020-08-04 . FARFAR2: Improved De Novo Rosetta Prediction of Complex Global RNA Folds . Structure . English . 28 . 8 . 963–976.e6 . 10.1016/j.str.2020.05.011 . 0969-2126 . 32531203. 7415647 . free .
45. Sharma S, Ding F, Dokholyan NV . iFoldRNA: three-dimensional RNA structure prediction and folding . Bioinformatics . 24 . 17 . 1951–1952 . September 2008 . 18579566 . 2559968 . 10.1093/bioinformatics/btn328 .
46. Parisien M, Major F . The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data . Nature . 452 . 7183 . 51–55 . March 2008 . 18322526 . 10.1038/nature06684 . 4415777 . 2008Natur.452...51P .
47. Jonikas MA, Radmer RJ, Laederach A, Das R, Pearlman S, Herschlag D, Altman RB . Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters . RNA . 15 . 2 . 189–199 . February 2009 . 19144906 . 2924536 . 10.1261/rna.1270809 .
48. Flores SC, Altman RB . Turning limited experimental information into 3D models of RNA . RNA . 16 . 9 . 1769–1778 . September 2010 . 20651028 . 2648710 . 10.1261/rna.2112110 .
49. Popenda M, Szachniuk M, Antczak M, Purzycka KJ, Lukasiak P, Bartol N, Blazewicz J, Adamiak RW . 6 . Automated 3D structure composition for large RNAs . Nucleic Acids Research . 40 . 14 . e112 . August 2012 . 22539264 . 3413140 . 10.1093/nar/gks339 .
50. Number of sequences:
51. Alignment: predicts an alignment,
52. Structure: predicts structure,
53. Knots: Pseudoknot prediction,
54. DR Bohdan . GI Nikolaev . JM Bujnicki . EF Baulin . SQUARNA - an RNA secondary structure prediction method based on a greedy stem formation model . August 2023 . 10.1101/2023.08.28.555103 . free .
55. Perriquet O, Touzet H, Dauchet M . Finding the common structure shared by two homologous RNAs . Bioinformatics . 19 . 1 . 108–116 . January 2003 . 12499300 . 10.1093/bioinformatics/19.1.108 . free .
56. Touzet H, Perriquet O . CARNAC: folding families of related RNAs . Nucleic Acids Research . 32 . Web Server issue . W142–W145 . July 2004 . 15215367 . 441553 . 10.1093/nar/gkh415 . 32 .
57. Hamada M, Sato K, Asai K . Improving the accuracy of predicting secondary structure for aligned RNA sequences . Nucleic Acids Research . 39 . 2 . 393–402 . January 2011 . 20843778 . 3025558 . 10.1093/nar/gkq792 .
58. Hamada M, Sato K, Kiryu H, Mituyama T, Asai K . CentroidAlign: fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score . Bioinformatics . 25 . 24 . 3236–3243 . December 2009 . 19808876 . 10.1093/bioinformatics/btp580 . free .
59. Yao Z, Weinberg Z, Ruzzo WL . CMfinder--a covariance model based RNA motif finding algorithm . Bioinformatics . 22 . 4 . 445–452 . February 2006 . 16357030 . 10.1093/bioinformatics/btk008 . free .
60. Dowell RD, Eddy SR . Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints . BMC Bioinformatics . 7 . 1 . 400 . September 2006 . 16952317 . 1579236 . 10.1186/1471-2105-7-400 . free .
61. Sato K, Kato Y, Akutsu T, Asai K, Sakakibara Y . DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition . Bioinformatics . 28 . 24 . 3218–3224 . December 2012 . 23060618 . 10.1093/bioinformatics/bts612 . free .
62. Mathews DH, Turner DH . Dynalign: an algorithm for finding the secondary structure common to two RNA sequences . Journal of Molecular Biology . 317 . 2 . 191–203 . March 2002 . 11902836 . 10.1006/jmbi.2001.5351 .
63. Mathews DH . Predicting a set of minimal free energy RNA secondary structures common to two sequences . Bioinformatics . 21 . 10 . 2246–2253 . May 2005 . 15731207 . 10.1093/bioinformatics/bti349 . free .
64. Harmanci AO, Sharma G, Mathews DH . Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign . BMC Bioinformatics . 8 . 1 . 130 . April 2007 . 17445273 . 1868766 . 10.1186/1471-2105-8-130 . free .
65. Sundfeld D, Havgaard JH, de Melo AC, Gorodkin J . Foldalign 2.5: multithreaded implementation for pairwise structural RNA alignment . Bioinformatics . 32 . 8 . 1238–1240 . April 2016 . 26704597 . 4824132 . 10.1093/bioinformatics/btv748 .
66. Torarinsson E, Havgaard JH, Gorodkin J . Multiple structural alignment and clustering of RNA sequences . Bioinformatics . 23 . 8 . 926–932 . April 2007 . 17324941 . 10.1093/bioinformatics/btm049 . free .
67. Book: Milo N, Zakov S, Katzenelson E, Bachmat E, Dinitz Y, Ziv-Ukelson M . Algorithms in Bioinformatics . RNA Tree Comparisons via Unrooted Unordered Alignments . 7534 . 135–148 . 2012 . 10.1007/978-3-642-33122-0_11 . Lecture Notes in Computer Science . 978-3-642-33121-3 .
68. Milo N, Zakov S, Katzenelson E, Bachmat E, Dinitz Y, Ziv-Ukelson M . Unrooted unordered homeomorphic subtree alignment of RNA trees . Algorithms for Molecular Biology . 8 . 1 . 13 . April 2013 . 23590940 . 3765143 . 10.1186/1748-7188-8-13 . free .
69. Heyne S, Costa F, Rose D, Backofen R . GraphClust: alignment-free structural clustering of local RNA secondary structures . Bioinformatics . 28 . 12 . i224–i232 . June 2012 . 22689765 . 3371856 . 10.1093/bioinformatics/bts224 .
70. Bindewald E, Shapiro BA . RNA secondary structure prediction from sequence alignments using a network of k-nearest neighbor classifiers . RNA . 12 . 3 . 342–352 . March 2006 . 16495232 . 1383574 . 10.1261/rna.2164906 .
71. Bauer M, Klau GW, Reinert K . Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization . BMC Bioinformatics . 8 . 1 . 271 . July 2007 . 17662141 . 1955456 . 10.1186/1471-2105-8-271 . free .
72. Will S, Reiche K, Hofacker IL, Stadler PF, Backofen R . Inferring noncoding RNA families and classes by means of genome-scale structure-based clustering . PLOS Computational Biology . 3 . 4 . e65 . April 2007 . 17432929 . 1851984 . 10.1371/journal.pcbi.0030065 . 2007PLSCB...3...65W . free .
73. Lindgreen S, Gardner PP, Krogh A . Measuring covariation in RNA alignments: physical realism improves information measures . Bioinformatics . 22 . 24 . 2988–2995 . December 2006 . 17038338 . 10.1093/bioinformatics/btl514 . free .
74. Lindgreen S, Gardner PP, Krogh A . MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing . Bioinformatics . 23 . 24 . 3304–3311 . December 2007 . 18006551 . 10.1093/bioinformatics/btm525 . 10.1.1.563.7072 .
75. Xu Z, Mathews DH . Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequences . Bioinformatics . 27 . 5 . 626–632 . March 2011 . 21193521 . 3042186 . 10.1093/bioinformatics/btq726 .
76. Kiryu H, Tabei Y, Kin T, Asai K . Murlet: a practical multiple alignment tool for structural RNA sequences . Bioinformatics . 23 . 13 . 1588–1598 . July 2007 . 17459961 . 10.1093/bioinformatics/btm146 . free .
77. Tabei Y, Kiryu H, Kin T, Asai K . A fast structural multiple alignment method for long RNA sequences . BMC Bioinformatics . 9 . 1 . 33 . January 2008 . 18215258 . 2375124 . 10.1186/1471-2105-9-33 . free .
78. Harmanci AO, Sharma G, Mathews DH . PARTS: probabilistic alignment for RNA joinT secondary structure prediction . Nucleic Acids Research . 36 . 7 . 2406–2417 . April 2008 . 18304945 . 2367733 . 10.1093/nar/gkn043 .
79. Knudsen B, Hein J . RNA secondary structure prediction using stochastic context-free grammars and evolutionary history . Bioinformatics . 15 . 6 . 446–454 . June 1999 . 10383470 . 10.1093/bioinformatics/15.6.446 . free .
80. Knudsen B, Hein J . Pfold: RNA secondary structure prediction using stochastic context-free grammars . Nucleic Acids Research . 31 . 13 . 3423–3428 . July 2003 . 12824339 . 169020 . 10.1093/nar/gkg614 .
81. Seemann SE, Gorodkin J, Backofen R . Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments . Nucleic Acids Research . 36 . 20 . 6355–6362 . November 2008 . 18836192 . 2582601 . 10.1093/nar/gkn544 .
82. Doose G, Metzler D . Bayesian sampling of evolutionarily conserved RNA secondary structures with pseudoknots . Bioinformatics . 28 . 17 . 2242–2248 . September 2012 . 22796961 . 10.1093/bioinformatics/bts369 . free .
83. Hofacker IL, Bernhart SH, Stadler PF . Alignment of RNA base pairing probability matrices . Bioinformatics . 20 . 14 . 2222–2227 . September 2004 . 15073017 . 10.1093/bioinformatics/bth229 . free .
84. Wei D, Alpert LV, Lawrence CE . RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences . Bioinformatics . 27 . 18 . 2486–2493 . September 2011 . 21788211 . 3167047 . 10.1093/bioinformatics/btr421 .
85. Wilm A, Higgins DG, Notredame C . R-Coffee: a method for multiple alignment of non-coding RNA . Nucleic Acids Research . 36 . 9 . e52 . May 2008 . 18420654 . 2396437 . 10.1093/nar/gkn174 .
86. Moretti S, Wilm A, Higgins DG, Xenarios I, Notredame C . R-Coffee: a web server for accurately aligning noncoding RNA sequences . Nucleic Acids Research . 36 . Web Server issue . W10–W13 . July 2008 . 18483080 . 2447777 . 10.1093/nar/gkn278 .
87. Harmanci AO, Sharma G, Mathews DH . TurboFold: iterative probabilistic estimation of secondary structures for multiple RNA sequences . BMC Bioinformatics . 12 . 1 . 108 . April 2011 . 21507242 . 3120699 . 10.1186/1471-2105-12-108 . free .
88. Seetin MG, Mathews DH . TurboKnot: rapid prediction of conserved RNA secondary structures including pseudoknots . Bioinformatics . 28 . 6 . 792–798 . March 2012 . 22285566 . 3307117 . 10.1093/bioinformatics/bts044 .
89. Rivas E, Clements J, Eddy SR . A statistical test for conserved RNA structure shows lack of evidence for structure in lncRNAs . Nature Methods . 14 . 1 . 45–48 . January 2017 . 27819659 . 5554622 . 10.1038/nmeth.4066 .
90. Hofacker IL, Fekete M, Stadler PF . Secondary structure prediction for aligned RNA sequences . Journal of Molecular Biology . 319 . 5 . 1059–1066 . June 2002 . 12079347 . 10.1016/S0022-2836(02)00308-X .
91. Voss B . Structural analysis of aligned RNAs . Nucleic Acids Research . 34 . 19 . 5471–5481 . 2006 . 17020924 . 1636479 . 10.1093/nar/gkl692 .
92. Reeder J, Giegerich R . Consensus shapes: an alternative to the Sankoff algorithm for RNA consensus structure prediction . Bioinformatics . 21 . 17 . 3516–3523 . September 2005 . 16020472 . 10.1093/bioinformatics/bti577 . free .
93. Höchsmann M, Töller T, Giegerich R, Kurtz S . Local similarity in RNA secondary structures . Proceedings. IEEE Computer Society Bioinformatics Conference . 2 . 159–168 . 2003 . 16452790 .
94. Höchsmann M, Voss B, Giegerich R . Pure multiple RNA secondary structure alignments: a progressive profile approach . IEEE/ACM Transactions on Computational Biology and Bioinformatics . 1 . 1 . 53–62 . 2004 . 17048408 . 10.1109/TCBB.2004.11 . 692442 .
95. Hamada M, Tsuda K, Kudo T, Kin T, Asai K . Mining frequent stem patterns from unaligned RNA sequences . Bioinformatics . 22 . 20 . 2480–2487 . October 2006 . 16908501 . 10.1093/bioinformatics/btl431 . free .
96. Xu X, Ji Y, Stormo GD . RNA Sampler: a new sampling based algorithm for common RNA secondary structure prediction and structural alignment . Bioinformatics . 23 . 15 . 1883–1891 . August 2007 . 17537756 . 10.1093/bioinformatics/btm272 . free .
97. Tabei Y, Tsuda K, Kin T, Asai K . SCARNA: fast and accurate structural alignment of RNA sequences by matching fixed-length stem fragments . Bioinformatics . 22 . 14 . 1723–1729 . July 2006 . 16690634 . 10.1093/bioinformatics/btl177 . free .
98. Meyer IM, Miklós I . SimulFold: simultaneously inferring RNA structures including pseudoknots, alignments, and trees using a Bayesian MCMC framework . PLOS Computational Biology . 3 . 8 . e149 . August 2007 . 17696604 . 1941756 . 10.1371/journal.pcbi.0030149 . 2007PLSCB...3..149M . free .
99. Holmes I . Accelerated probabilistic inference of RNA structure evolution . BMC Bioinformatics . 6 . 1 . 73 . March 2005 . 15790387 . 1090553 . 10.1186/1471-2105-6-73 . free .
100. Dalli D, Wilm A, Mainz I, Steger G . STRAL: progressive alignment of non-coding RNA using base pairing probability vectors in quadratic time . Bioinformatics . 22 . 13 . 1593–1599 . July 2006 . 16613908 . 10.1093/bioinformatics/btl142 . free .
101. Engelen S, Tahi F . Tfold: efficient in silico prediction of non-coding RNA secondary structures . Nucleic Acids Research . 38 . 7 . 2453–2466 . April 2010 . 20047957 . 2853104 . 10.1093/nar/gkp1067 .
102. Torarinsson E, Lindgreen S . WAR: Webserver for aligning structural RNAs . Nucleic Acids Research . 36 . Web Server issue . W79–W84 . July 2008 . 18492721 . 2447782 . 10.1093/nar/gkn275 .
103. Klosterman PS, Uzilov AV, Bendaña YR, Bradley RK, Chao S, Kosiol C, Goldman N, Holmes I . 6 . XRate: a fast prototyping, training and annotation tool for phylo-grammars . BMC Bioinformatics . 7 . 1 . 428 . October 2006 . 17018148 . 1622757 . 10.1186/1471-2105-7-428 . free .
104. Web site: https://academic.oup.com/bioinformatics/article/34/13/i70/5045712 . 2023-01-10 . academic.oup.com.
105. Web site: https://academic.oup.com/nargab/article/2/4/lqaa086/5940903 . 2023-01-10 . academic.oup.com.
106. Hanumanthappa AK, Singh J, Paliwal K, Singh J, Zhou Y . Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network . Bioinformatics . 36 . 21 . 5169–5176 . January 2021 . 33106872 . 10.1093/bioinformatics/btaa652 . free . 10072/399087 . free .
107. Sun S, Wu Q, Peng Z, Yang J . Enhanced prediction of RNA solvent accessibility with long short-term memory neural networks and improved sequence profiles . Bioinformatics . 35 . 10 . 1686–1691 . May 2019 . 30321300 . 10.1093/bioinformatics/bty876 .
108. Yang Y, Li X, Zhao H, Zhan J, Wang J, Zhou Y . Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction . RNA . 23 . 1 . 14–22 . January 2017 . 27807179 . 5159645 . 10.1261/rna.057364.116 .
109. DR Bohdan . GI Nikolaev . JM Bujnicki . EF Baulin . SQUARNA - an RNA secondary structure prediction method based on a greedy stem formation model . August 2023 . 10.1101/2023.08.28.555103 . free .
110. Eggenhofer F, Tafer H, Stadler PF, Hofacker IL . RNApredator: fast accessibility-based prediction of sRNA targets . Nucleic Acids Research . 39 . Web Server issue . W149–W154 . July 2011 . 21672960 . 3125805 . 10.1093/nar/gkr467 .
111. Gerlach W, Giegerich R . GUUGle: a utility for fast exact matching under RNA complementary rules including G-U base pairing . Bioinformatics . 22 . 6 . 762–764 . March 2006 . 16403789 . 10.1093/bioinformatics/btk041 . free .
112. Mann M, Wright PR, Backofen R . IntaRNA 2.0: enhanced and customizable prediction of RNA-RNA interactions . Nucleic Acids Research . 45 . W1 . W435–W439 . July 2017 . 28472523 . 5570192 . 10.1093/nar/gkx279 .
113. Wright PR, Georg J, Mann M, Sorescu DA, Richter AS, Lott S, Kleinkauf R, Hess WR, Backofen R . 6 . CopraRNA and IntaRNA: predicting small RNA targets, networks and interaction domains . Nucleic Acids Research . 42 . Web Server issue . W119–W123 . July 2014 . 24838564 . 4086077 . 10.1093/nar/gku359 .
114. Busch A, Richter AS, Backofen R . IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions . Bioinformatics . 24 . 24 . 2849–2856 . December 2008 . 18940824 . 2639303 . 10.1093/bioinformatics/btn544 .
115. Richter AS, Schleberger C, Backofen R, Steglich C . Seed-based INTARNA prediction combined with GFP-reporter system identifies mRNA targets of the small RNA Yfr1 . Bioinformatics . 26 . 1 . 1–5 . January 2010 . 19850757 . 2796815 . 10.1093/bioinformatics/btp609 .
116. Smith C, Heyne S, Richter AS, Will S, Backofen R . Freiburg RNA Tools: a web server integrating INTARNA, EXPARNA and LOCARNA . Nucleic Acids Research . 38 . Web Server issue . W373–W377 . July 2010 . 20444875 . 2896085 . 10.1093/nar/gkq316 .
117. Wright PR, Richter AS, Papenfort K, Mann M, Vogel J, Hess WR, Backofen R, Georg J . 6 . 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 . September 2013 . 23980183 . 3773804 . 10.1073/pnas.1303248110 . free . 2013PNAS..110E3487W .
118. Wright PR, Georg J, Mann M, Sorescu DA, Richter AS, Lott S, Kleinkauf R, Hess WR, Backofen R . 6 . CopraRNA and IntaRNA: predicting small RNA targets, networks and interaction domains . Nucleic Acids Research . 42 . Web Server issue . W119–W123 . July 2014 . 24838564 . 4086077 . 10.1093/nar/gku359 .
119. Górska A, Jasiński M, Trylska J . MINT: software to identify motifs and short-range interactions in trajectories of nucleic acids . Nucleic Acids Research . 43 . 17 . e114 . September 2015 . 26024667 . 4787793 . 10.1093/nar/gkv559 .
120. 10.1137/060651100 . Dirks RM, Bois JS, Schaeffer JM, Winfree E, Pierce NA . Thermodynamic Analysis of Interacting Nucleic Acid Strands . SIAM Review . 49 . 1 . 65–88 . 2007. 2007SIAMR..49...65D. 10.1.1.523.4764 .
121. Mathews DH, Burkard ME, Freier SM, Wyatt JR, Turner DH . Predicting oligonucleotide affinity to nucleic acid targets . RNA . 5 . 11 . 1458–1469 . November 1999 . 10580474 . 1369867 . 10.1017/S1355838299991148 .
122. Chitsaz H, Salari R, Sahinalp SC, Backofen R . A partition function algorithm for interacting nucleic acid strands . Bioinformatics . 25 . 12 . i365–i373 . June 2009 . 19478011 . 2687966 . 10.1093/bioinformatics/btp212 .
123. Monga I, Banerjee I. Computational Identification of piRNAs Using Features Based on RNA Sequence, Structure, Thermodynamic and Physicochemical Properties . Current Genomics . 20 . 7 . 508–518 . November 2019 . 32655289. 10.2174/1389202920666191129112705 . 7327968 .
124. Li AX, Marz M, Qin J, Reidys CM . RNA-RNA interaction prediction based on multiple sequence alignments . Bioinformatics . 27 . 4 . 456–463 . February 2011 . 21134894 . 10.1093/bioinformatics/btq659 . 1003.3987 . 6586629 .
125. Kato Y, Sato K, Hamada M, Watanabe Y, Asai K, Akutsu T . RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming . Bioinformatics . 26 . 18 . i460–i466 . September 2010 . 20823308 . 2935440 . 10.1093/bioinformatics/btq372 .
126. Bernhart SH, Tafer H, Mückstein U, Flamm C, Stadler PF, Hofacker IL . Partition function and base pairing probabilities of RNA heterodimers . Algorithms for Molecular Biology . 1 . 1 . 3 . March 2006 . 16722605 . 1459172 . 10.1186/1748-7188-1-3 . free .
127. Rehmsmeier M, Steffen P, Hochsmann M, Giegerich R . Fast and effective prediction of microRNA/target duplexes . RNA . 10 . 10 . 1507–1517 . October 2004 . 15383676 . 1370637 . 10.1261/rna.5248604 .
128. Krüger J, Rehmsmeier M . RNAhybrid: microRNA target prediction easy, fast and flexible . Nucleic Acids Research . 34 . Web Server issue . W451–W454 . July 2006 . 16845047 . 1538877 . 10.1093/nar/gkl243 .
129. Mückstein U, Tafer H, Hackermüller J, Bernhart SH, Stadler PF, Hofacker IL . Thermodynamics of RNA-RNA binding . Bioinformatics . 22 . 10 . 1177–1182 . May 2006 . 16446276 . 10.1093/bioinformatics/btl024 . free .
130. Chorostecki U, Palatnik JF . comTAR: a web tool for the prediction and characterization of conserved microRNA targets in plants . Bioinformatics . 30 . 14 . 2066–2067 . July 2014 . 24632500 . 10.1093/bioinformatics/btu147 . free . 11336/29681 . free .
131. Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, Lim B, Rigoutsos I . 6 . A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes . Cell . 126 . 6 . 1203–1217 . September 2006 . 16990141 . 10.1016/j.cell.2006.07.031 . free .
132. Weill N, Lisi V, Scott N, Dallaire P, Pelloux J, Major F . MiRBooking simulates the stoichiometric mode of action of microRNAs . Nucleic Acids Research . 43 . 14 . 6730–6738 . August 2015 . 26089388 . 4538818 . 10.1093/nar/gkv619 .
133. Baek D, Villén J, Shin C, Camargo FD, Gygi SP, Bartel DP . The impact of microRNAs on protein output . Nature . 455 . 7209 . 64–71 . September 2008 . 18668037 . 2745094 . 10.1038/nature07242 . 2008Natur.455...64B .
134. Alexiou P, Maragkakis M, Papadopoulos GL, Reczko M, Hatzigeorgiou AG . Lost in translation: an assessment and perspective for computational microRNA target identification . Bioinformatics . 25 . 23 . 3049–3055 . December 2009 . 19789267 . 10.1093/bioinformatics/btp565 . free .
135. Ritchie W, Flamant S, Rasko JE . Predicting microRNA targets and functions: traps for the unwary . Nature Methods . 6 . 6 . 397–398 . June 2009 . 19478799 . 10.1038/nmeth0609-397 . 205417583 .
136. Chiu HS, Llobet-Navas D, Yang X, Chung WJ, Ambesi-Impiombato A, Iyer A, Kim HR, Seviour EG, Luo Z, Sehgal V, Moss T, Lu Y, Ram P, Silva J, Mills GB, Califano A, Sumazin P . 6 . Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks . Genome Research . 25 . 2 . 257–267 . February 2015 . 25378249 . 4315299 . 10.1101/gr.178194.114 .
137. Maragkakis M, Alexiou P, Papadopoulos GL, Reczko M, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, Simossis VA, Sethupathy P, Vergoulis T, Koziris N, Sellis T, Tsanakas P, Hatzigeorgiou AG . 6 . Accurate microRNA target prediction correlates with protein repression levels . BMC Bioinformatics . 10 . 1 . 295 . September 2009 . 19765283 . 2752464 . 10.1186/1471-2105-10-295 . free .
138. Thadani R, Tammi MT . MicroTar: predicting microRNA targets from RNA duplexes . BMC Bioinformatics . 7 . Suppl 5 . S20 . December 2006 . 17254305 . 1764477 . 10.1186/1471-2105-7-S5-S20 . 7 . free .
139. Kim SK, Nam JW, Rhee JK, Lee WJ, Zhang BT . miTarget: microRNA target gene prediction using a support vector machine . BMC Bioinformatics . 7 . 1 . 411 . September 2006 . 16978421 . 1594580 . 10.1186/1471-2105-7-411 . free .
140. Friedman Y, Naamati G, Linial M . MiRror: a combinatorial analysis web tool for ensembles of microRNAs and their targets . Bioinformatics . 26 . 15 . 1920–1921 . August 2010 . 20529892 . 10.1093/bioinformatics/btq298 . free .
141. Balaga O, Friedman Y, Linial M . Toward a combinatorial nature of microRNA regulation in human cells . Nucleic Acids Research . 40 . 19 . 9404–9416 . October 2012 . 22904063 . 3479204 . 10.1093/nar/gks759 .
142. Krek A, Grün D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, Rajewsky N . 6 . Combinatorial microRNA target predictions . Nature Genetics . 37 . 5 . 495–500 . May 2005 . 15806104 . 10.1038/ng1536 . 22672750 .
143. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E . The role of site accessibility in microRNA target recognition . Nature Genetics . 39 . 10 . 1278–1284 . October 2007 . 17893677 . 10.1038/ng2135 . 1721807 .
144. Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, Lim B, Rigoutsos I . 6 . A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes . Cell . 126 . 6 . 1203–1217 . September 2006 . 16990141 . 10.1016/j.cell.2006.07.031 . free .
145. van Dongen S, Abreu-Goodger C, Enright AJ . Detecting microRNA binding and siRNA off-target effects from expression data . Nature Methods . 5 . 12 . 1023–1025 . December 2008 . 18978784 . 2635553 . 10.1038/nmeth.1267 .
146. Bartonicek N, Enright AJ . SylArray: a web server for automated detection of miRNA effects from expression data . Bioinformatics . 26 . 22 . 2900–2901 . November 2010 . 20871108 . 10.1093/bioinformatics/btq545 . free .
147. Heikham R, Shankar R . Flanking region sequence information to refine microRNA target predictions . Journal of Biosciences . 35 . 1 . 105–118 . March 2010 . 20413915 . 10.1007/s12038-010-0013-7 . amp . 7047781 .
148. Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB . Prediction of mammalian microRNA targets . Cell . 115 . 7 . 787–798 . December 2003 . 14697198 . 10.1016/S0092-8674(03)01018-3 . free .
149. Lewis BP, Burge CB, Bartel DP . Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets . Cell . 120 . 1 . 15–20 . January 2005 . 15652477 . 10.1016/j.cell.2004.12.035 . free .
150. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP . MicroRNA targeting specificity in mammals: determinants beyond seed pairing . Molecular Cell . 27 . 1 . 91–105 . July 2007 . 17612493 . 3800283 . 10.1016/j.molcel.2007.06.017 .
151. Garcia DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP . 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 . September 2011 . 21909094 . 3190056 . 10.1038/nsmb.2115 .
152. Agarwal V, Bell GW, Nam JW, Bartel DP . Predicting effective microRNA target sites in mammalian mRNAs . eLife . 4 . e05005 . August 2015 . 26267216 . 4532895 . 10.7554/eLife.05005 . free .
153. Agarwal V, Subtelny AO, Thiru P, Ulitsky I, Bartel DP . Predicting microRNA targeting efficacy in Drosophila . Genome Biology . 19 . 1 . 152 . October 2018 . 30286781 . 6172730 . 10.1186/s13059-018-1504-3 . free .
154. Number of sequences:
155. Alignment: predicts an alignment,
156. Structure: predicts structure,
157. Washietl S, Hofacker IL . 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 . September 2004 . 15313604 . 10.1016/j.jmb.2004.07.018 . 10.1.1.58.6251 .
158. Pedersen JS, Bejerano G, Siepel A, Rosenbloom K, Lindblad-Toh K, Lander ES, Kent J, Miller W, Haussler D . 6 . Identification and classification of conserved RNA secondary structures in the human genome . PLOS Computational Biology . 2 . 4 . e33 . April 2006 . 16628248 . 1440920 . 10.1371/journal.pcbi.0020033 . 2006PLSCB...2...33P . free .
159. Heyne S, Costa F, Rose D, Backofen R . GraphClust: alignment-free structural clustering of local RNA secondary structures . Bioinformatics . 28 . 12 . i224–i232 . June 2012 . 22689765 . 3371856 . 10.1093/bioinformatics/bts224 .
160. Coventry A, Kleitman DJ, Berger B . 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 . August 2004 . 15304649 . 514400 . 10.1073/pnas.0404193101 . free . 2004PNAS..10112102C .
161. Rivas E, Eddy SR . Noncoding RNA gene detection using comparative sequence analysis . BMC Bioinformatics . 2 . 1 . 8 . 2001 . 11801179 . 64605 . 10.1186/1471-2105-2-8 . free .
162. Rivas E, Klein RJ, Jones TA, Eddy SR . Computational identification of noncoding RNAs in E. coli by comparative genomics . Current Biology . 11 . 17 . 1369–1373 . September 2001 . 11553332 . 10.1016/S0960-9822(01)00401-8 . free . 2001CBio...11.1369R .
163. Washietl S, Hofacker IL, Stadler PF . Fast and reliable prediction of noncoding RNAs . Proceedings of the National Academy of Sciences of the United States of America . 102 . 7 . 2454–2459 . February 2005 . 15665081 . 548974 . 10.1073/pnas.0409169102 . free . 2005PNAS..102.2454W .
164. Gruber AR, Neuböck R, Hofacker IL, Washietl S . The RNAz web server: prediction of thermodynamically stable and evolutionarily conserved RNA structures . Nucleic Acids Research . 35 . Web Server issue . W335–W338 . July 2007 . 17452347 . 1933143 . 10.1093/nar/gkm222 .
165. Book: Washietl S . Comparative Genomics . Prediction of Structural Noncoding RNAs with RNAz . 395 . 503–26 . 2007 . 17993695 . 10.1007/978-1-59745-514-5_32. Methods in Molecular Biology . 978-1-58829-693-1 .
166. Andrews RJ, Roche J, Moss WN . ScanFold: an approach for genome-wide discovery of local RNA structural elements-applications to Zika virus and HIV . PeerJ . 6 . e6136 . 2018 . 30627482 . 6317755 . 10.7717/peerj.6136 . free .
167. Laslett D, Canback B . ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences . Nucleic Acids Research . 32 . 1 . 11–16 . 2004 . 14704338 . 373265 . 10.1093/nar/gkh152 .
168. Jha A, Shankar R . miReader: Discovering Novel miRNAs in Species without Sequenced Genome . PLOS ONE . 8 . 6 . e66857 . 2013 . 23805282 . 3689854 . 10.1371/journal.pone.0066857 . free . 2013PLoSO...866857J .
169. Artzi S, Kiezun A, Shomron N . miRNAminer: a tool for homologous microRNA gene search . BMC Bioinformatics . 9 . 1 . 39 . January 2008 . 18215311 . 2258288 . 10.1186/1471-2105-9-39 . free .
170. Ahmed F, Ansari HR, Raghava GP . Prediction of guide strand of microRNAs from its sequence and secondary structure . BMC Bioinformatics . 10 . 1 . 105 . April 2009 . 19358699 . 2676257 . 10.1186/1471-2105-10-105 . free .
171. Hertel J, Stadler PF . Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data . Bioinformatics . 22 . 14 . e197–e202 . July 2006 . 16873472 . 10.1093/bioinformatics/btl257 . free .
172. Wuyts J, Perrière G, Van De Peer Y . The European ribosomal RNA database . Nucleic Acids Research . 32 . Database issue . D101–D103 . January 2004 . 14681368 . 308799 . 10.1093/nar/gkh065 .
173. Szymanski M, Barciszewska MZ, Erdmann VA, Barciszewski J . 5S Ribosomal RNA Database . Nucleic Acids Research . 30 . 1 . 176–178 . January 2002 . 11752286 . 99124 . 10.1093/nar/30.1.176 .
174. Lagesen K, Hallin P, Rødland EA, Staerfeldt HH, Rognes T, Ussery DW . RNAmmer: consistent and rapid annotation of ribosomal RNA genes . Nucleic Acids Research . 35 . 9 . 3100–3108 . 2007 . 17452365 . 1888812 . 10.1093/nar/gkm160 .
175. Hertel J, Hofacker IL, Stadler PF . SnoReport: computational identification of snoRNAs with unknown targets . Bioinformatics . 24 . 2 . 158–164 . January 2008 . 17895272 . 10.1093/bioinformatics/btm464 . free .
176. Lowe TM, Eddy SR . A computational screen for methylation guide snoRNAs in yeast . Science . 283 . 5405 . 1168–1171 . February 1999 . 10024243 . 10.1126/science.283.5405.1168 . 1999Sci...283.1168L .
177. Schattner P, Brooks AN, Lowe TM . The tRNAscan-SE, snoscan and snoGPS web servers for the detection of tRNAs and snoRNAs . Nucleic Acids Research . 33 . Web Server issue . W686–W689 . July 2005 . 15980563 . 1160127 . 10.1093/nar/gki366 .
178. Lowe TM, Eddy SR . tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence . Nucleic Acids Research . 25 . 5 . 955–964 . March 1997 . 9023104 . 146525 . 10.1093/nar/25.5.955 .
179. Tempel S, Tahi F . A fast ab-initio method for predicting miRNA precursors in genomes . Nucleic Acids Research . 40 . 11 . e80 . June 2012 . 22362754 . 3367186 . 10.1093/nar/gks146 .
180. Wright ES . FindNonCoding: rapid and simple detection of non-coding RNAs in genomes . Bioinformatics . Oct12 . 3. 841–843 . October 2021 . 34636849 . 10.1093/bioinformatics/btab708 . 10060727 .
181. Gautheret D, Lambert A . Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles . Journal of Molecular Biology . 313 . 5 . 1003–1011 . November 2001 . 11700055 . 10.1006/jmbi.2001.5102 .
182. Lambert A, Fontaine JF, Legendre M, Leclerc F, Permal E, Major F, Putzer H, Delfour O, Michot B, Gautheret D . 6 . The ERPIN server: an interface to profile-based RNA motif identification . Nucleic Acids Research . 32 . Web Server issue . W160–W165 . July 2004 . 15215371 . 441556 . 10.1093/nar/gkh418 .
183. Lambert A, Legendre M, Fontaine JF, Gautheret D . Computing expectation values for RNA motifs using discrete convolutions . BMC Bioinformatics . 6 . 1 . 118 . May 2005 . 15892887 . 1168889 . 10.1186/1471-2105-6-118 . free .
184. Nawrocki EP, Eddy SR . Query-dependent banding (QDB) for faster RNA similarity searches . PLOS Computational Biology . 3 . 3 . e56 . March 2007 . 17397253 . 1847999 . 10.1371/journal.pcbi.0030056 . 2007PLSCB...3...56N . free .
185. Eddy SR . A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure . BMC Bioinformatics . 3 . 1 . 18 . July 2002 . 12095421 . 119854 . 10.1186/1471-2105-3-18 . free .
186. Eddy SR, Durbin R . RNA sequence analysis using covariance models . Nucleic Acids Research . 22 . 11 . 2079–2088 . June 1994 . 8029015 . 308124 . 10.1093/nar/22.11.2079 .
187. Heyne S, Costa F, Rose D, Backofen R . GraphClust: alignment-free structural clustering of local RNA secondary structures . Bioinformatics . 28 . 12 . i224–i232 . June 2012 . 22689765 . 3371856 . 10.1093/bioinformatics/bts224 .
188. Sato K, Sakakibara Y . RNA secondary structural alignment with conditional random fields . Bioinformatics . 21 . suppl_2 . ii237–ii242 . September 2005 . 16204111 . 10.1093/bioinformatics/bti1139 . 21 . free .
189. Weinberg Z, Ruzzo WL . Exploiting conserved structure for faster annotation of non-coding RNAs without loss of accuracy . Bioinformatics . 20 . suppl_1 . i334–i341 . August 2004 . 15262817 . 10.1093/bioinformatics/bth925 . 20 . free .
190. Weinberg Z, Ruzzo WL . Sequence-based heuristics for faster annotation of non-coding RNA families . Bioinformatics . 22 . 1 . 35–39 . January 2006 . 16267089 . 10.1093/bioinformatics/bti743 . free .
191. Klein RJ, Eddy SR . RSEARCH: finding homologs of single structured RNA sequences . BMC Bioinformatics . 4 . 1 . 44 . September 2003 . 14499004 . 239859 . 10.1186/1471-2105-4-44 . free .
192. Meyer F, Kurtz S, Backofen R, Will S, Beckstette M . Structator: fast index-based search for RNA sequence-structure patterns . BMC Bioinformatics . 12 . 1 . 214 . May 2011 . 21619640 . 3154205 . 10.1186/1471-2105-12-214 . free .
193. Meyer F, Kurtz S, Beckstette M . Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns . En . BMC Bioinformatics . 14 . 1 . 226 . July 2013 . 23865810 . 3765529 . 10.1186/1471-2105-14-226 . free .
194. Structure: benchmarks structure prediction tools
195. Alignment: benchmarks alignment tools
196. Gardner PP, Giegerich R . A comprehensive comparison of comparative RNA structure prediction approaches . BMC Bioinformatics . 5 . 1 . 140 . September 2004 . 15458580 . 526219 . 10.1186/1471-2105-5-140 . free .
197. Gardner PP, Wilm A, Washietl S . A benchmark of multiple sequence alignment programs upon structural RNAs . Nucleic Acids Research . 33 . 8 . 2433–2439 . 2005 . 15860779 . 1087786 . 10.1093/nar/gki541 .
198. Wilm A, Mainz I, Steger G . An enhanced RNA alignment benchmark for sequence alignment programs . Algorithms for Molecular Biology . 1 . 1 . 19 . October 2006 . 17062125 . 1635699 . 10.1186/1748-7188-1-19 . free .
199. Freyhult EK, Bollback JP, Gardner PP . Exploring genomic dark matter: a critical assessment of the performance of homology search methods on noncoding RNA . Genome Research . 17 . 1 . 117–125 . January 2007 . 17151342 . 1716261 . 10.1101/gr.5890907 .
200. Puton T, Kozlowski LP, Rother KM, Bujnicki JM . CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction . Nucleic Acids Research . 41 . 7 . 4307–4323 . April 2013 . 23435231 . 3627593 . 10.1093/nar/gkt101 .
201. Wright ES . RNAconTest: comparing tools for noncoding RNA multiple sequence alignment based on structural consistency . RNA . 26 . 5 . 531–540 . May 2020 . 32005745 . 7161358 . 10.1261/rna.073015.119 .
202. Alignment: view and edit an alignment,
203. Structure: view and edit structure,
204. Seibel PN, Müller T, Dandekar T, Schultz J, Wolf M . 4SALE--a tool for synchronous RNA sequence and secondary structure alignment and editing . BMC Bioinformatics . 7 . 1 . 498 . November 2006 . 17101042 . 1637121 . 10.1186/1471-2105-7-498 . free .
205. Bendaña YR, Holmes IH . Colorstock, SScolor, Ratón: RNA alignment visualization tools . Bioinformatics . 24 . 4 . 579–580 . February 2008 . 18218657 . 7109877 . 10.1093/bioinformatics/btm635 . free .
206. Nicol JW, Helt GA, Blanchard SG, Raja A, Loraine AE . The Integrated Genome Browser: free software for distribution and exploration of genome-scale datasets . Bioinformatics . 25 . 20 . 2730–2731 . October 2009 . 19654113 . 2759552 . 10.1093/bioinformatics/btp472 .
207. Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ . Jalview Version 2--a multiple sequence alignment editor and analysis workbench . Bioinformatics . 25 . 9 . 1189–1191 . May 2009 . 19151095 . 2672624 . 10.1093/bioinformatics/btp033 .
208. Clamp M, Cuff J, Searle SM, Barton GJ . The Jalview Java alignment editor . Bioinformatics . 20 . 3 . 426–427 . February 2004 . 14960472 . 10.1093/bioinformatics/btg430 . free .
209. Griffiths-Jones S . RALEE--RNA ALignment editor in Emacs . Bioinformatics . 21 . 2 . 257–259 . January 2005 . 15377506 . 10.1093/bioinformatics/bth489 . free .
210. Andersen ES, Lind-Thomsen A, Knudsen B, Kristensen SE, Havgaard JH, Torarinsson E, Larsen N, Zwieb C, Sestoft P, Kjems J, Gorodkin J . 6 . Semiautomated improvement of RNA alignments . RNA . 13 . 11 . 1850–1859 . November 2007 . 17804647 . 2040093 . 10.1261/rna.215407 .
211. Lee J, Kladwang W, Lee M, Cantu D, Azizyan M, Kim H, Limpaecher A, Yoon S, Treuille A, Das R . 6 . 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 . February 2014 . 24469816 . 3926058 . 10.1073/pnas.1313039111 . free . 2014PNAS..111.2122L .
212. Garcia-Martin JA, Clote P, Dotu I . RNAiFOLD: a constraint programming algorithm for RNA inverse folding and molecular design . Journal of Bioinformatics and Computational Biology . 11 . 2 . 1350001 . April 2013 . 23600819 . 10.1142/S0219720013500017 .
213. Garcia-Martin JA, Clote P, Dotu I . RNAiFold: a web server for RNA inverse folding and molecular design . Nucleic Acids Research . 41 . Web Server issue . W465–W470 . July 2013 . 23700314 . 3692061 . 10.1093/nar/gkt280 .
214. Garcia-Martin JA, Dotu I, Clote P . RNAiFold 2.0: a web server and software to design custom and Rfam-based RNA molecules . Nucleic Acids Research . 43 . W1 . W513–W521 . July 2015 . 26019176 . 4489274 . 10.1093/nar/gkv460 . 1505.04210 . 2015arXiv150504210G .
215. Andronescu M, Fejes AP, Hutter F, Hoos HH, Condon A . A new algorithm for RNA secondary structure design . Journal of Molecular Biology . 336 . 3 . 607–624 . February 2004 . 15095976 . 10.1016/j.jmb.2003.12.041 .
216. Busch A, Backofen R . INFO-RNA--a fast approach to inverse RNA folding . Bioinformatics . 22 . 15 . 1823–1831 . August 2006 . 16709587 . 10.1093/bioinformatics/btl194 . amp . free .
217. Busch A, Backofen R . INFO-RNA--a server for fast inverse RNA folding satisfying sequence constraints . Nucleic Acids Research . 35 . Web Server issue . W310–W313 . July 2007 . 17452349 . 1933236 . 10.1093/nar/gkm218 . amp .
218. Avihoo A, Churkin A, Barash D . RNAexinv: An extended inverse RNA folding from shape and physical attributes to sequences . BMC Bioinformatics . 12 . 319 . 319 . August 2011 . 21813013 . 3176266 . 10.1186/1471-2105-12-319 . amp . free .
219. Levin A, Lis M, Ponty Y, O'Donnell CW, Devadas S, Berger B, Waldispühl J . A global sampling approach to designing and reengineering RNA secondary structures . Nucleic Acids Research . 40 . 20 . 10041–10052 . November 2012 . 22941632 . 3488226 . 10.1093/nar/gks768 . amp .
220. Reinharz V, Ponty Y, Waldispühl J . A weighted sampling algorithm for the design of RNA sequences with targeted secondary structure and nucleotide distribution . Bioinformatics . 29 . 13 . i308–i315 . July 2013 . 23812999 . 3694657 . 10.1093/bioinformatics/btt217 . amp .
221. Matthies MC, Bienert S, Torda AE . Dynamics in Sequence Space for RNA Secondary Structure Design . Journal of Chemical Theory and Computation . 8 . 10 . 3663–3670 . October 2012 . 26593011 . 10.1021/ct300267j . amp .
222. Taneda A . MODENA: a multi-objective RNA inverse folding . Advances and Applications in Bioinformatics and Chemistry . 4 . 1–12 . 2011 . 21918633 . 3169953 . 10.2147/aabc.s14335 . free .
223. Taneda A . Multi-objective genetic algorithm for pseudoknotted RNA sequence design . Frontiers in Genetics . 3 . 36 . 2012 . 22558001 . 3337422 . 10.3389/fgene.2012.00036 . free .
224. Esmaili-Taheri A, Ganjtabesh M, Mohammad-Noori M . Evolutionary solution for the RNA design problem . Bioinformatics . 30 . 9 . 1250–1258 . May 2014 . 24407223 . 10.1093/bioinformatics/btu001 . free .
225. Kleinkauf R, Mann M, Backofen R . antaRNA: ant colony-based RNA sequence design . Bioinformatics . 31 . 19 . 3114–3121 . October 2015 . 26023105 . 4576691 . 10.1093/bioinformatics/btv319 .
226. Kleinkauf R, Houwaart T, Backofen R, Mann M . antaRNA--Multi-objective inverse folding of pseudoknot RNA using ant-colony optimization . BMC Bioinformatics . 16 . 389 . 389 . November 2015 . 26581440 . 4652366 . 10.1186/s12859-015-0815-6 . free .
227. Flamm C, Hofacker IL, Maurer-Stroh S, Stadler PF, Zehl M . Design of multistable RNA molecules . RNA . 7 . 2 . 254–265 . February 2001 . 11233982 . 1370083 . 10.1017/s1355838201000863 .
228. Rodrigo G, Jaramillo A . RiboMaker: computational design of conformation-based riboregulation . Bioinformatics . 30 . 17 . 2508–2510 . September 2014 . 24833802 . 10.1093/bioinformatics/btu335 . amp . free .
229. Hammer S, Tschiatschek B, Flamm C, Hofacker IL, Findeiß S . RNAblueprint: flexible multiple target nucleic acid sequence design . Bioinformatics . 33 . 18 . 2850–2858 . September 2017 . 28449031 . 5870862 . 10.1093/bioinformatics/btx263 . amp .
230. Höner zu Siederdissen C, Hammer S, Abfalter I, Hofacker IL, Flamm C, Stadler PF . Computational design of RNAs with complex energy landscapes . Biopolymers . 99 . 12 . 1124–1136 . December 2013 . 23818234 . 10.1002/bip.22337 . amp . 7337968 .
231. Lyngsø RB, Anderson JW, Sizikova E, Badugu A, Hyland T, Hein J . Frnakenstein: multiple target inverse RNA folding . BMC Bioinformatics . 13 . 260 . 260 . October 2012 . 23043260 . 3534541 . 10.1186/1471-2105-13-260 . amp . free .
232. Shu W, Liu M, Chen H, Bo X, Wang S . ARDesigner: a web-based system for allosteric RNA design . Journal of Biotechnology . 150 . 4 . 466–473 . December 2010 . 20969900 . 10.1016/j.jbiotec.2010.10.067 .
233. Byun Y, Han K . PseudoViewer3: generating planar drawings of large-scale RNA structures with pseudoknots . Bioinformatics . 25 . 11 . 1435–1437 . June 2009 . 19369500 . 10.1093/bioinformatics/btp252 . free .
234. Byun Y, Han K . PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structures . Nucleic Acids Research . 34 . Web Server issue . W416–W422 . July 2006 . 16845039 . 1538805 . 10.1093/nar/gkl210 .
235. Han K, Byun Y . PSEUDOVIEWER2: Visualization of RNA pseudoknots of any type . Nucleic Acids Research . 31 . 13 . 3432–3440 . July 2003 . 12824341 . 168946 . 10.1093/nar/gkg539 .
236. Han K, Lee Y, Kim W . PseudoViewer: automatic visualization of RNA pseudoknots . Bioinformatics . 18 . Suppl 1 . S321–S328 . 2002 . 12169562 . 10.1093/bioinformatics/18.suppl_1.S321 . 18 . free .
237. Kaiser A, Krüger J, Evers DJ . RNA Movies 2: sequential animation of RNA secondary structures . Nucleic Acids Research . 35 . Web Server issue . W330–W334 . July 2007 . 17567618 . 1933240 . 10.1093/nar/gkm309 .
238. Evers D, Giegerich R . RNA movies: visualizing RNA secondary structure spaces . Bioinformatics . 15 . 1 . 32–37 . January 1999 . 10068690 . 10.1093/bioinformatics/15.1.32 . free .
239. Book: Tsang HH, Dai DC . Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine . RNA-DV . 2012. 601–603. 10.1145/2382936.2383036 . 978-1-4503-1670-5. 15910737.
240. Martinez HM, Maizel JV, Shapiro BA . RNA2D3D: a program for generating, viewing, and comparing 3-dimensional models of RNA . Journal of Biomolecular Structure & Dynamics . 25 . 6 . 669–683 . June 2008 . 18399701 . 3727907 . 10.1080/07391102.2008.10531240 .
241. Reuter JS, Mathews DH . RNAstructure: software for RNA secondary structure prediction and analysis . BMC Bioinformatics . 11 . 1 . 129 . March 2010 . 20230624 . 2984261 . 10.1186/1471-2105-11-129 . free .
242. Yang H, Jossinet F, Leontis N, Chen L, Westbrook J, Berman H, Westhof E . Tools for the automatic identification and classification of RNA base pairs . Nucleic Acids Research . 31 . 13 . 3450–3460 . July 2003 . 12824344 . 168936 . 10.1093/nar/gkg529 .
243. Menzel P, Seemann SE, Gorodkin J . RILogo: visualizing RNA-RNA interactions . Bioinformatics . 28 . 19 . 2523–2526 . October 2012 . 22826541 . 10.1093/bioinformatics/bts461 . free .
244. Darty K, Denise A, Ponty Y . VARNA: Interactive drawing and editing of the RNA secondary structure . Bioinformatics . 25 . 15 . 1974–1975 . August 2009 . 19398448 . 2712331 . 10.1093/bioinformatics/btp250 .
245. Kerpedjiev P, Hammer S, Hofacker IL . Forna (force-directed RNA): Simple and effective online RNA secondary structure diagrams . Bioinformatics . 31 . 20 . 3377–3379 . October 2015 . 26099263 . 4595900 . 10.1093/bioinformatics/btv372 .
246. Weinberg Z, Breaker RR . R2R--software to speed the depiction of aesthetic consensus RNA secondary structures . BMC Bioinformatics . 12 . 1 . 3 . January 2011 . 21205310 . 3023696 . 10.1186/1471-2105-12-3 . free .
247. Johnson PZ, Simon AE . RNAcanvas: interactive drawing and exploration of nucleic acid structures . Nucleic Acids Research . 51 . w1 . W501–W508 . July 2023 . 37094080 . 10320051 . 10.1093/nar/gkad302 .
248. Mitra . Raktim . Cohen . Ari S . Rohs . Remo . 2024-04-17 . RNAscape: geometric mapping and customizable visualization of RNA structure . Nucleic Acids Research . 10.1093/nar/gkae269 . 0305-1048. free . 11223802 .