List of RNA structure prediction software

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

RNA structure
prediction.

Single sequence secondary structure prediction.

Name Description Knots
[Note 1] 		Links References
SQUARNA Secondary structure prediction based on a greedy stem formation model Yes sourcecode [1]
CentroidFold Secondary structure prediction based on generalized centroid estimator No sourcecode webserver [2]
CentroidHomfold Secondary structure prediction by using homologous sequence information No sourcecode webserver [3]
Context Fold An RNA secondary structure prediction software based on feature-rich trained scoring models. No sourcecode webserver [4]
CONTRAfold Secondary structure prediction method based on conditional log-linear models (CLLMs), a flexible class of probabilistic models which generalize upon
feature-rich
scoring.		 No sourcecode webserver [5]
Crumple
 Simple, cleanly written software to produce the full set of possible secondary structures for one sequence, given optional constraints. No sourcecode [6]
CyloFold Secondary structure prediction method based on placement of helices allowing complex pseudoknots. Yes webserver [7]
E2Efold A deep learning based method for efficiently predicting secondary structure by differentiating through a constrained optimization solver, without using dynamic programming. Yes sourcecode [8][9]
EternaFold A multitask-learning-based model trained on data from the Eterna project. No sourcecode webserver [10]
GTFold Fast and scalable multicore code for predicting RNA secondary structure. No link sourcecode [11]
INTERPIN Algorithm and database for prediction of transcription termination sites in bacteria. Uses Mfold for RNA secondary structure prediction. No webserver [12][13]
IPknot Fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming. Yes sourcecode webserver [14]
KineFold Folding kinetics of RNA sequences including pseudoknots by including an implementation of the partition function for knots. Yes linuxbinary, webserver [15][16]
Mfold MFE (Minimum Free Energy) RNA structure prediction algorithm. No sourcecode, webserver [17]
pKiss A dynamic programming algorithm for the prediction of a restricted class (H-type and kissing hairpins) of RNA pseudoknots. Yes sourcecode, webserver [18]
Pknots A dynamic programming algorithm for optimal RNA pseudoknot prediction using the nearest neighbour energy model. Yes sourcecode [19]
PknotsRG A dynamic programming algorithm for the prediction of a restricted class (H-type) of RNA pseudoknots. Yes sourcecode, webserver [20]
RNA123 Secondary structure prediction via thermodynamic-based folding algorithms and novel structure-based sequence alignment specific for RNA. Yes webserver
RNAfold MFE RNA structure prediction algorithm. Includes an implementation of the partition function for computing basepair probabilities and circular RNA folding. No sourcecode, webserver

[17][21][22][23][24]

RNAshapes MFE RNA structure prediction based on abstract shapes. Shape abstraction retains adjacency and nesting of structural features, but disregards helix lengths, thus reduces the number of suboptimal solutions without losing significant information. Furthermore, shapes represent classes of structures for which probabilities based on Boltzmann-weighted energies can be computed. No source & binaries, webserver [25][26]
RNAstructure A program to predict lowest free energy structures and base pair probabilities for RNA or DNA sequences. Programs are also available to predict maximum expected accuracy structures and these can include pseudoknots. Structure prediction can be constrained using experimental data, including SHAPE, enzymatic cleavage, and chemical modification accessibility. Graphical user interfaces are available for Windows, Mac OS X, Linux. Programs are also available for use with Unix-style text interfaces. Also, a C++ class library is available. Yes source & binaries, webserver

[27][28]

SARNA-Predict RNA Secondary structure prediction method based on simulated annealing. It can also predict structure with pseudoknots. Yes link [29]
seqfold Predict the minimum free energy structure of nucleic acids. seqfold is an implementation of the Zuker, 1981 dynamic programming algorithm, the basis for UNAFold/mfold, with energy functions from SantaLucia, 2004 (DNA) and Turner, 2009 (RNA). MIT license. Python CLI or module. No link & source [30]
Sfold Statistical sampling of all possible structures. The sampling is weighted by partition function probabilities. No Github_Repository [31][32][33][34]
Sliding Windows & Assembly Sliding windows and assembly is a tool chain for folding long series of similar hairpins. No sourcecode [6]
SPOT-RNA SPOT-RNA is first RNA secondary structure predictor which can predict all kind base pairs (canonical, noncanonical, pseudoknots, and base triplets). Yes sourcecode

webserver

[35]
SwiSpot Command-line utility for predicting alternative (secondary) configurations of riboswitches. It is based on the prediction of the so-called switching sequence, to subsequently constrain the folding of the two functional structures. No sourcecode [36]
UFold UFold: fast and accurate RNA secondary structure prediction with deep learning Yes sourcecode, webserver [37]
UNAFold Command-line utility for predicting alternative (secondary) configurations of riboswitches. It is based on the prediction of the so-called switching sequence, to subsequently constrain the folding of the two functional structures. No sourcecode [38]
vsfold/vs subopt Folds and predicts RNA secondary structure and pseudoknots using an entropy model derived from polymer physics. The program vs_subopt computes suboptimal structures based on the free energy landscape derived from vsfold5. Yes webserver [39][40]
Notes
  1. ^ Knots: Pseudoknot prediction, <yes|no>.

Single sequence tertiary structure prediction

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

Comparative methods

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

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

webserver

[98][99]
Notes
  1. ^ Number of sequences: <any|num>.
  2. ^ Alignment: predicts an alignment, <input|yes|no>.
  3. structure
    , <input|yes|no>.
  4. ^ Knots: Pseudoknot prediction, <yes|no>.

RNA solvent accessibility prediction

Name

(Year)

Description Link References
RNAsnap2

(2020)

RNAsnap2 uses a dilated convolutional neural network with evolutionary features generated from BLAST + INFERNAL (same as RNAsol) and predicted base-pairing probabilities from LinearPartition as an input for the prediction of RNA solvent accessibility. Also, the single-sequence version of RNAsnap2 can predict the solvent accessibility of a given input RNA sequence without using evolutionary information. sourcecode

webserver

[100]
RNAsol

(2019)

RNAsol predictor uses a unidirectional LSTM deep learning algorithm with evolutionary information generated from BLASTN + INFERNAL and predicted secondary structure from RNAfold as an input for the prediction of RNA solvent accessibility. sourcecode

webserver

[101]
RNAsnap

(2017)

RNAsnap predictor uses an SVM machine learning algorithm and evolutionary information generated from BLASTN as an input for the prediction of RNA solvent accessibility. sourcecode [102]

Intermolecular interactions: RNA-RNA

Many

RyhB
.

Name Description Intra-molecular structure Comparative Link References
SQUARNA SQUARNA predicts RNA secondary structure formed by several RNA sequences using a greedy stem formation model Yes Yes sourcecode [1]
RNApredator RNApredator uses a dynamic programming approach to compute RNA-RNA interaction sites. Yes No webserver [103]
GUUGle A utility for fast determination of RNA-RNA matches with perfect hybridization via A-U, C-G, and G-U base pairing. No No webserver [104]
IntaRNA Efficient target prediction incorporating the accessibility of target sites. Yes No sourcecode webserver [105][106][107][108][109]
CopraRNA Tool for sRNA target prediction. It computes whole genome predictions by mix of distinct whole genome IntaRNA predictions. Yes Yes sourcecode webserver [110][106]
MINT Automatic tool to analyze three-dimensional structures of RNA and DNA molecules, their full-atom molecular dynamics trajectories or other conformation sets (e.g. X-ray or NMR-derived structures). For each RNA or DNA conformation MINT determines the hydrogen bonding network resolving the base pairing patterns, identifies secondary structure motifs (helices, junctions, loops, etc.) and pseudoknots. Also estimates the energy of stacking and phosphate anion-base interactions. Yes No sourcecode webserver [111]
NUPACK Computes the full unpseudoknotted partition function of interacting strands in dilute solution. Calculates the concentrations, mfes, and base-pairing probabilities of the ordered complexes below a certain complexity. Also computes the partition function and basepairing of single strands including a class of pseudoknotted structures. Also enables design of ordered complexes. Yes No NUPACK [112]
OligoWalk/RNAstructure Predicts bimolecular secondary structures with and without intramolecular structure. Also predicts the hybridization affinity of a short nucleic acid to an RNA target. Yes No [1] [113]
piRNA
 Calculates the partition function and thermodynamics of RNA-RNA interactions. It considers all possible joint secondary structure of two interacting nucleic acids that do not contain pseudoknots, interaction pseudoknots, or zigzags. Yes No linuxbinary [114]
piRNAPred an integrated framework for piRNA prediction employing hybrid features like k-mer nucleotide composition, secondary structure, thermodynamic and physicochemical properties. Yes No [2] [115]
RNAripalign Calculates the partition function and thermodynamics of RNA-RNA interactions based on structural alignments. Also supports RNA-RNA interaction prediction for single sequences. It outputs suboptimal structures based on Boltzmann distribution. It considers all possible joint secondary structure of two interacting nucleic acids that do not contain pseudoknots, interaction pseudoknots, or zigzags. Yes No [3] [116]
RactIP Fast and accurate prediction of RNA-RNA interaction using integer programming. Yes No sourcecode webserver [117]
RNAaliduplex Based on RNAduplex with bonuses for covarying sites No Yes sourcecode [21]
RNAcofold Works much like RNAfold, but allows specifying two RNA sequences which are then allowed to form a dimer structure. Yes No sourcecode [21][118]
RNAduplex Computes optimal and suboptimal secondary structures for hybridization. The calculation is simplified by allowing only inter-molecular base pairs. No No sourcecode [21]
RNAhybrid Tool to find the minimum free energy hybridisation of a long and a short RNA (≤ 30 nt). No No sourcecode, webserver [119][120]
RNAup Calculates the thermodynamics of RNA-RNA interactions. RNA-RNA binding is decomposed into two stages. (1) First the probability that a sequence interval (e.g. a binding site) remains unpaired is computed. (2) Then the binding energy given that the binding site is unpaired is calculated as the optimum over all possible types of bindings. Yes No sourcecode [21][121]

Intermolecular interactions: MicroRNA:any RNA

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

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

Intermolecular interactions: MicroRNA:UTR

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

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

ncRNA gene prediction software

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

Family specific gene prediction software

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

RNA homology search software

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

Benchmarks

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

Alignment viewers, editors

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

Inverse folding, RNA design

Name Description Link References
Single state design
EteRNA/EteRNABot An RNA folding game that challenges players to make sequences that fold into a target RNA structure. The best sequences for a given puzzle are synthesized and their structures are probed through chemical mapping. The sequences are then scored by the data's agreement to the target structure and feedback is provided to the players. EteRNABot is a software implementation based on design rules submitted by EteRNA players. EteRNA Game EteRNABot web server [193]
RNAinverse The ViennaRNA Package provides RNAinverse, an algorithm for designing sequences with desired structure. Web Server [21]
RNAiFold A complete RNA inverse folding approach based on constraint programming and implemented using OR Tools which allows for the specification of a wide range of design constraints. The RNAiFold software provides two algorithms to solve the inverse folding problem: i) RNA-CPdesign explores the complete search space and ii) RNA-LNSdesign based on the large neighborhood search metaheuristic is suitable to design large structures. The software can also design interacting RNA molecules using RNAcofold of the ViennaRNA Package. A fully functional, earlier implementation using COMET is available. Web Server Source Code [194][195][196]
RNA-SSD/RNA Designer The RNA-SSD (RNA Secondary Structure Designer) approach first assigns bases probabilistically to each position based probabilistic models. Subsequently, a stochastic local search is used to optimize this sequence. RNA-SSD is publicly available under the name of RNA Designer at the RNASoft web page Web Server [197]
INFO-RNA INFO-RNA uses a dynamic programming approach to generate an energy optimized starting sequence that is subsequently further improved by a stochastic local search that uses an effective neighbor selection method. Web Server Source Code [198][199]
RNAexinv RNAexinv is an extension of RNAinverse to generate sequences that not only fold into a desired structure, but they should also exhibit selected attributes such as thermodynamic stability and mutational robustness. This approach does not necessarily outputs a sequence that perfectly fits the input structure, but a shape abstraction, i.e. it keeps the adjacency and nesting of structural elements, but disregards helix lengths and the exact number unpaired positions, of it. Source Code [200]
RNA-ensign This approach applies an efficient global sampling algorithm to examine the mutational landscape under structural and thermodynamical constraints. The authors show that the global sampling approach is more robust, succeeds more often and generates more thermodynamically stable sequences than local approaches do. Source Code [201]
IncaRNAtion Successor of RNA-ensign that can specifically design sequences with a specified GC content using a GC-weighted Boltzmann ensemble and stochastic backtracking Source Code [202]
DSS-Opt Dynamics in Sequence Space Optimization (DSS-Opt) uses Newtonian dynamics in the sequence space, with a negative design term and simulated annealing to optimize a sequence such that it folds into the desired secondary structure. Source Code [203]
MODENA This approach interprets RNA inverse folding as a multi-objective optimization problem and solves it using a genetic algorithm. In its extended version MODENA is able to design pseudoknotted RNA structures with the aid of IPknot. Source Code [204][205]
ERD Evolutionary RNA Design (ERD) can be used to design RNA sequences that fold into a given target structure. Any RNA secondary structure contains different structural components, each having a different length. Therefore, in the first step, the RNA subsequences (pools) corresponding to different components with different lengths are reconstructed. Using these pools, ERD reconstructs an initial RNA sequence which is compatible with the given target structure. Then ERD uses an evolutionary algorithm to improve the quality of the subsequences corresponding to the components. The major contributions of ERD are using the natural RNA sequences, a different method to evaluate the sequences in each population, and a different hierarchical decomposition of the target structure into smaller substructures. Web Server Source Code [206]
antaRNA Uses an underlying ant colony foraging heuristic terrain modeling to solve the inverse folding problem. The designed RNA sequences show high compliance to input structural and sequence constraints. Most prominently, also the GC value of the designed sequence can be regulated with high precision. GC value distribution sampling of solution sets is possible and sequence domain specific definition of multiple GC values within one entity. Due to the flexible evaluation of the intermediate sequences using underlying programs such as RNAfold, pKiss, or also HotKnots and IPKnot, RNA secondary nested structures and also pseudoknot structures of H- and K-type are feasible to solve with this approach. Web Server Source Code [207][208]
Dual state design
switch.pl The ViennaRNA Package provides a Perl script to design RNA sequences that can adopt two states. For instance RNA thermometer, which change their structural state depending on the environmental temperature, have been successfully designed using this program. Man Page Source Code [209]
RiboMaker Intended to design small RNAs (sRNA) and their target mRNA's 5'UTR. The sRNA is designed to activate or repress protein expression of the mRNA. It is also possible to design just one of the two RNA components provided the other sequence is fixed. Web Server Source Code [210]
Multi state design
RNAblueprint This C++ library is based on the RNAdesign multiple target sampling algorithm. It brings a SWIG interface for Perl and Python which allows for an effortless integration into various tools. Therefore, multiple target sequence sampling can be combined with many optimization techniques and objective functions. Source Code [211]
RNAdesign The underlying algorithm is based on a mix of graph coloring and heuristic local optimization to find sequences can adapt multiple prescribed conformations. The software can also use of RNAcofold to design interacting RNA sequence pairs. Source Code[permanent dead link] [212]
Frnakenstein Frnakenstein applies a genetic algorithm to solve the inverse RNA folding problem. Source Code [213]
ARDesigner The Allosteric RNA Designer (ARDesigner) is a web-based tool that solves the inverse folding problem by incorporating mutational robustness. Beside a local search the software has been equipped with a simulated annealing approach to effectively search for good solutions. The tool has been used to design RNA thermometer. [4][dead link] [214]
Notes

Secondary structure viewers, editors

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

sourcecode

[230]

See also

References

  1. ^
    doi:10.1101/2023.08.28.555103. {{cite journal}}: Cite journal requires |journal= (help
    )
  2. PMID 19095700
    .
  3. PMID 19478007
    .
  4. PMID 22035327
    .
  5. PMID 16873527
    .
  6. ^
    PMID 21723827
    .
  7. PMID 20501603
    .
  8. arXiv:2002.05810 [cs.LG
    ].
  9. ^ Chen, X., Li, Y., Umarov, R., Gao, X., and Song, L. RNAsecondary structure prediction by learning unrolled algorithms. In International Conference on Learning Representations, 2020. URL https://openreview.net/forum?id=S1eALyrYDH.
  10. PMID 36192461
    .
  11. PMID 22747589
    .
  12. PMID 37499897
    .
  13. PMID 34376740
    .
  14. PMID 21685106
    .
  15. PMID 15980546
    .
  16. PMID 14676318
    .
  17. ^
    PMID 6163133
    .
  18. ^
    ISBN 978-3-642-15293-1
    .
  19. S2CID 2228845
    .
  20. PMID 17478505
    .
  21. ^
    S2CID 19344304
    .
  22. S2CID 12629688
    .
  23. PMID 16452114
    .
  24. S2CID 15637111
    .
  25. PMID 15371549
    .
  26. PMID 16480488
    .
  27. PMID 15123812
    .
  28. PMID 15272118
    .
  29. S2CID 12095376
    .
  30. ^ seqfold, Lattice Automation, 2022-03-27, retrieved 2022-03-27
  31. PMID 14654704
    .
  32. PMID 15215366
    .
  33. PMID 16043502
    .
  34. PMID 16109749
    .
  35. PMID 31776342
    .
  36. PMID 27378291
    .
  37. PMID 34792173
    .
  38. PMID 18712296
    .
  39. PMID 17878940
    .
  40. doi:10.4081/jnai.2014.2652
    .
  41. PMID 37945552
    .
  42. PMID 19543381
    .
  43. PMID 32531203
    .
  44. PMID 18579566
    .
  45. S2CID 4415777
    .
  46. PMID 19144906
    .
  47. PMID 20651028
    .
  48. PMID 22539264
    .
  49. PMID 12499300
    .
  50. PMID 15215367
    .
  51. PMID 20843778
    .
  52. PMID 19808876
    .
  53. PMID 16357030
    .
  54. PMID 16952317
    .
  55. PMID 23060618
    .
  56. PMID 11902836
    .
  57. PMID 15731207
    .
  58. PMID 17445273
    .
  59. PMID 26704597
    .
  60. PMID 17324941
    .
  61. ISBN 978-3-642-33121-3
    .
  62. PMID 23590940
    .
  63. ^
    PMID 22689765
    .
  64. PMID 16495232
    .
  65. PMID 17662141
    .
  66. PMID 17432929
    .
  67. PMID 17038338
    .
  68. PMID 18006551
    .
  69. PMID 21193521
    .
  70. PMID 17459961
    .
  71. PMID 18215258
    .
  72. PMID 18304945
    .
  73. PMID 10383470
    .
  74. PMID 12824339
    .
  75. PMID 18836192
    .
  76. PMID 22796961
    .
  77. PMID 15073017
    .
  78. PMID 21788211
    .
  79. PMID 18420654
    .
  80. PMID 18483080
    .
  81. PMID 21507242
    .
  82. PMID 22285566
    .
  83. PMID 27819659
    .
  84. PMID 12079347
    .
  85. PMID 17020924
    .
  86. PMID 16020472
    .
  87. PMID 16452790
    .
  88. S2CID 692442
    .
  89. PMID 16908501
    .
  90. PMID 17537756
    .
  91. PMID 16690634
    .
  92. PMID 17696604
    .
  93. PMID 15790387
    .
  94. PMID 16613908
    .
  95. PMID 20047957
    .
  96. PMID 18492721
    .
  97. ^
    PMID 17018148
    .
  98. ^ academic.oup.com https://academic.oup.com/bioinformatics/article/34/13/i70/5045712. Retrieved 2023-01-10. {{cite web}}: Missing or empty |title= (help)
  99. ^ academic.oup.com https://academic.oup.com/nargab/article/2/4/lqaa086/5940903. Retrieved 2023-01-10. {{cite web}}: Missing or empty |title= (help)
  100. PMID 33106872
    .
  101. PMID 30321300
    .
  102. PMID 27807179
    .
  103. PMID 21672960
    .
  104. PMID 16403789
    .
  105. PMID 28472523
    .
  106. ^
    PMID 24838564
    .
  107. PMID 18940824
    .
  108. PMID 19850757
    .
  109. PMID 20444875
    .
  110. PMID 23980183
    .
  111. PMID 26024667
    .
  112. doi:10.1137/060651100
    .
  113. PMID 10580474
    .
  114. PMID 19478011
    .
  115. PMID 32655289
    .
  116. S2CID 6586629
    .
  117. PMID 20823308
    .
  118. PMID 16722605
    .
  119. ^
    PMID 15383676
    .
  120. ^
    PMID 16845047
    .
  121. PMID 16446276
    .
  122. PMID 24632500
    .
  123. ^
    PMID 16990141
    .
  124. PMID 26089388
    .
  125. PMID 18668037
    .
  126. PMID 19789267
    .
  127. S2CID 205417583
    .
  128. PMID 25378249
    .
  129. PMID 19765283
    .
  130. PMID 17254305
    .
  131. PMID 16978421
    .
  132. PMID 20529892
    .
  133. PMID 22904063
    .
  134. S2CID 22672750
    .
  135. S2CID 1721807
    .
  136. PMID 18978784
    .
  137. PMID 20871108
    .
  138. S2CID 7047781
    .
  139. PMID 14697198
    .
  140. PMID 15652477
    .
  141. PMID 17612493
    .
  142. PMID 21909094
    .
  143. PMID 26267216
    .
  144. PMID 30286781
    .
  145. PMID 15313604
    .
  146. PMID 16628248
    .
  147. PMID 15304649
    .
  148. PMID 11801179
    .
  149. PMID 11553332
    .
  150. PMID 15665081
    .
  151. PMID 17452347
    .
  152. PMID 17993695
    .
  153. PMID 30627482
    .
  154. PMID 14704338
    .
  155. PMID 23805282
    .
  156. PMID 18215311
    .
  157. PMID 19358699
    .
  158. PMID 16873472
    .
  159. PMID 14681368
    .
  160. PMID 11752286
    .
  161. PMID 17452365
    .
  162. PMID 17895272
    .
  163. PMID 10024243
    .
  164. ^
    PMID 15980563
    .
  165. PMID 9023104
    .
  166. PMID 22362754
    .
  167. PMID 34636849
    .
  168. PMID 11700055
    .
  169. PMID 15215371
    .
  170. PMID 15892887
    .
  171. PMID 17397253
    .
  172. PMID 12095421
    .
  173. PMID 8029015
    .
  174. PMID 16204111
    .
  175. PMID 15262817
    .
  176. PMID 16267089
    .
  177. PMID 14499004
    .
  178. PMID 21619640
    .
  179. PMID 23865810
    .
  180. PMID 15458580
    .
  181. PMID 15860779
    .
  182. PMID 17062125
    .
  183. PMID 17151342
    .
  184. PMID 23435231
    .
  185. PMID 32005745
    .
  186. PMID 17101042
    .
  187. PMID 18218657
    .
  188. PMID 19654113
    .
  189. PMID 19151095
    .
  190. PMID 14960472
    .
  191. PMID 15377506
    .
  192. PMID 17804647
    .
  193. PMID 24469816
    .
  194. PMID 23600819
    .
  195. PMID 23700314
    .
  196. PMID 26019176
    .
  197. PMID 15095976
    .
  198. PMID 16709587
    .
  199. PMID 17452349
    .
  200. PMID 21813013
    .
  201. PMID 22941632
    .
  202. PMID 23812999
    .
  203. PMID 26593011
    .
  204. PMID 21918633
    .
  205. PMID 22558001
    .
  206. PMID 24407223
    .
  207. PMID 26023105
    .
  208. PMID 26581440
    .
  209. PMID 11233982
    .
  210. PMID 24833802
    .
  211. PMID 28449031
    .
  212. S2CID 7337968
    .
  213. PMID 23043260
    .
  214. PMID 20969900
    .
  215. PMID 19369500
    .
  216. PMID 16845039
    .
  217. PMID 12824341
    .
  218. PMID 12169562
    .
  219. PMID 17567618
    .
  220. PMID 10068690
    .
  221. S2CID 15910737
    .
  222. PMID 18399701
    .
  223. PMID 20230624
    .
  224. PMID 12824344
    .
  225. PMID 22826541
    .
  226. PMID 19398448
    .
  227. PMID 26099263
    .
  228. PMID 21205310
    .
  229. PMID 37094080
    .
  230. ISSN 0305-1048
    .
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