List of RNA structure prediction software

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

Single sequence secondary structure prediction

Name Description Knots
[Note 1]
Links References
CentroidFold Secondary structure prediction based on generalized centroid estimator no sourcecode webserver[1]
CentroidHomfold Secondary structure prediction by using homologous sequence information no sourcecode webserver [2]
Context Fold An RNA secondary structure prediction software based on feature-rich trained scoring models. no sourcecode webserver [3]
CONTRAfold Secondary structure prediction method based on conditional log-linear models (CLLMs), a flexible class of probabilistic models which generalize upon SCFGs by using discriminative training and feature-rich scoring. no sourcecode webserver[4]
CyloFold Secondary structure prediction method based on placement of helices allowing complex pseudoknots. yes webserver [5]
GTFold Fast and scalable multicore code for predicting RNA secondary structure. no link sourcecode [6]
IPknot Fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming. yes sourcecode webserver [7]
KineFold Folding kinetics of RNA sequences including pseudoknots by including an implementation of the partition function for knots.yeslinuxbinary, webserver[8][9]
Mfold MFE (Minimum Free Energy) RNA structure prediction algorithm. no sourcecode, webserver [10]
Pknots A dynamic programming algorithm for optimal RNA pseudoknot prediction using the nearest neighbour energy model. yessourcecode[11]
PknotsRG A dynamic programming algorithm for the prediction of a restricted class (H-type) of RNA pseudoknots.yessourcecode, webserver[12]
pKiss A dynamic programming algorithm for the prediction of a restricted class (H-type and kissing hairpins) of RNA pseudoknots.yessourcecode, webserver[13]
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

[10][14][15][16][17]

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 [18][19]
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 and for Mac OS-X/Linux. Programs are also available for use with Unix-style text interfaces. Additionally, a C++ class library is available. yes source & binaries, webserver

[20][21]

SARNA-Predict RNA Secondary structure prediction method based on simulated annealing. It can also predict structure with pseudoknots. yes link [22]
Sfold Statistical sampling of all possible structures. The sampling is weighted by partition function probabilities. no webserver[23][24][25][26]
UNAFold The UNAFold software package is an integrated collection of programs that simulate folding, hybridization, and melting pathways for one or two single-stranded nucleic acid sequences. no sourcecode [27]
Crumple Crumple is simple, cleanly written software for producing the full set of possible secondary structures for a single sequence, given optional constraints. no sourcecode [28]
Sliding Windows & Assembly Sliding windows and assembly is a tool chain for folding long series of similar hairpins. no sourcecode [28]
Notes
  1. Knots: Pseudoknot prediction, <yes|no>.

Single sequence tertiary structure prediction

Name Description Knots
[Note 1]
Links References
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 [29]
FARNA Automated de novo prediction of native-like RNA tertiary structures . yes [30]
iFoldRNA three-dimensional RNA structure prediction and folding yes webserver [31]
MC-Fold MC-Sym Pipeline Thermodynamics and Nucleotide cyclic motifs for RNA structure prediction algorithm. 2D and 3D structures. yes sourcecode, webserver [32]
NAST Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters ? executables [33]
MMB Turning limited experimental information into 3D models of RNA ? sourcecode [34]
RNA123 An 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 a single intuitive graphical user interface. yes
RNAComposer Fully automated prediction of large RNA 3D structures. yes webserver webserver [35]
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
Carnac Comparative analysis combined with MFE folding.anynoyesnosourcecode, webserver[36][37]
CentroidAlifold Common secondary structure prediction based on generalized centroid estimator anynoyesno sourcecode [38]
CentroidAlign Fast and accurate multiple aligner for RNA sequences anyyesnono sourcecode [39]
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.3\le seqs \le60yesyesnosourcecode, webserver, website [40]
CONSAN implements a pinned Sankoff algorithm for simultaneous pairwise RNA alignment and consensus structure prediction. 2 yes yes no sourcecode [41]
DAFS Simultaneous aligning and folding of RNA sequences via dual decomposition. any yes yes yes sourcecode [42]
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 [43][44][45]
FoldalignM A multiple RNA structural RNA alignment method, to a large extend based on the PMcomp program.anyyesyesno sourcecode [46]
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.anyyesinputnosourcecode, webserver [47][48]
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. anyyesyesno sourcecode [49]
KNetFold Computes a consensus RNA secondary structure from an RNA sequence alignment based on machine learning.anyinputyesyeslinuxbinary, webserver [50]
LARA Produce a global fold and alignment of ncRNA families using integer linear programming and Lagrangian relaxation.anyyesyesnosourcecode [51]
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 [52]
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.anyyesyesno sourcecode [53][54]
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 [55]
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 [56]
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 [57]
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 [13]
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 [58]
Pfold Folds alignments using a SCFG trained on rRNA alignments. \le40inputyesnowebserver[59][60]
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 [61]
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 [62]
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 2\le seqs \le6 yes yes no sourcecode, webserver [63]
RNAG A Gibbs sampling method to determine a conserved structure and the structural alignment. any yes yes no sourcecode [64]
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 [65][66]
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 [67][68]
RNA123 The structure based sequence alignment (SBSA) algorithm within RNA123 utilizes 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 utilizes two separate substitution matrices that are 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 (~2800 nts). any yes yes yes webserver
RNAalifold Folds precomputed alignments using a combination of free-energy and a covariation measures. Ships with the Vienna package. any input yes no homepage [14][69]
RNAalishapes A tool for secondary structure prediction for precomputed alignments using a combination of free-energy and a covariation measures. Output can be sifted by the abstract shapes concept to focus on major difference in sub-optimal results. any input yes no sourcecode, webserver [70]
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. anynoyesno sourcecode, webserver [71]
RNAforester Compare and align RNA secondary structures via a "forest alignment" approach.anyyesinputnosourcecode, webserver [72][73]
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 [74]
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 [75]
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.2yesyesno webserver [76]
SimulFold simultaneously inferring RNA structures including pseudoknots, alignments, and trees using a Bayesian MCMC framework. any yes yes yes sourcecode [77]
Stemloc a program for pairwise RNA structural alignment based on probabilistic models of RNA structure known as Pair stochastic context-free grammars.anyyesyesnosourcecode[78]
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.\le50yesnonosourcecode, webserver [79]
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. anyyesyesyeswebserver[80]
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. 2\le seqs \le50yesyesnowebserver[81]
Xrate a program for analysis of multiple sequence alignments using phylogenetic grammars, that may be viewed as a flexible generalization of the "Pfold" program.anyyesyesnosourcecode[82]
Notes
  1. Number of sequences: <any|num>.
  2. Alignment: predicts an alignment, <input|yes|no>.
  3. Structure: predicts structure, <input|yes|no>.
  4. Knots: Pseudoknot prediction, <yes|no>.

Inter molecular 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
RNApredator RNApredator uses a dynamic programming approach to compute RNA-RNA interaction sites. yes no webserver [83]
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 [84]
IntaRNA Efficient target prediction incorporating the accessibility of target sites. yes no sourcecode webserver [85][86][87][88]
CopraRNA CopraRNA is a tool for sRNA target prediction. It computes whole genome predictions by combination of distinct whole genome IntaRNA predictions. yes yes sourcecode webserver [89][85]
MINT MINT is an automatic tool for analyzing 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. MINT also estimates the energy of stacking and phosphate anion-base interactions. yes no sourcecode webserver [90]
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 [91]
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 [92]
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 [93]
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 [94]
RactIP Fast and accurate prediction of RNA-RNA interaction using integer programming. yes no sourcecode webserver [95]
RNAaliduplex Based upon RNAduplex with bonuses for covarying sites no yes sourcecode [14]
RNAcofold works much like RNAfold, but allows to specify two RNA sequences which are then allowed to form a dimer structure. yes no sourcecode [14][96]
RNAduplex computes optimal and suboptimal secondary structures for hybridization. The calculation is simplified by allowing only inter-molecular base pairs. no no sourcecode [14]
RNAhybrid a tool for finding the minimum free energy hybridisation of a long and a short RNA. no no sourcecode, webserver [97][98]
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 [14][99]

Inter molecular interactions: MicroRNA:any RNA

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

Name Description Species Specific Intra-molecular structure Comparative Link References
RNA22 The first link (precomputed predictions) provides RNA22 predictions for all protein coding transcripts in human, mouse, roundworm, and fruit fly. It allows you to visualize 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. no no no precomputed predictions interactive/custom sequences [100]
RNAhybrid a tool for finding the minimum free energy hybridisation of a long and a short RNA. no no no sourcecode, webserver [97][98]

Inter molecular 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),[101] (Alexiou et al., Bioinformatics 2009),[102] or (Ritchie et al., Nature Methods 2009)[103]

Name Description Species Specific Intra-molecular structure Comparative Link References
Cupid Cupid is a 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) [104]
Diana-microT DIANA-microT 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 [105]
MicroTar An animal miRNA target prediction tool based on miRNA-target complementarity and thermodynamic data. no no no sourcecode [106]
miTarget microRNA target gene prediction using a support vector machine. no no no webserver [107]
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 no no no webserver [108][109]
PicTar Combinatorial microRNA target predictions. 8 vertebrates no yes predictions [110]
PITA Incorporates the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition. no yes no executable, webserver, predictions [111]
RNA22 The first link (precomputed predictions) provides RNA22 predictions for all protein coding transcripts in human, mouse, roundworm, and fruit fly. It allows you to visualize 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. no no no precomputed predictions interactive/custom sequences [100]
RNAhybrid a tool for finding the minimum free energy hybridisation of a long and a short RNA. no no no sourcecode, webserver [97][98]
Sylamer Sylamer is a method for finding significantly over or under-represented words in sequences according to a sorted gene list. Typically it is used to find significant enrichment or depletion of microRNA or siRNA seed sequences from microarray expression data. no no no sourcecode webserver [112][113]
TAREF TAREF stands for TARget REFiner. It 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 [114]
p-TAREF p-TAREF stands for plant TARget REFiner. It 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 as well as 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. Besides this, it also provides an 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 better performing. 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 the predictions beyond conserved sites and consider all sites. vertebrates, flies, nematodes evaluated indirectly yes sourcecode, webserver [115][116][117][118][119]

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 [120]
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 [121]
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 [49]
MSARi heuristic search for statistically significant conservation of RNA secondary structure in deep multiple sequence alignments. any input yes sourcecode [122]
QRNA This is the code from Elena Rivas that accompanies a submitted manuscript "Noncoding RNA gene detection using camparative 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 [123][124]
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 [125][126][127]
Xrate a program for analysis of multiple sequence alignments using phylogenetic grammars, that may be viewed as a flexible generalization of the "Evofold" program.anyyesyessourcecode[82]
Notes
  1. Number of sequences: <any|num>.
  2. Alignment: predicts an alignment, <input|yes|no>.
  3. Structure: predicts structure, <input|yes|no>.

Family specific gene prediction software

Name Description Family Link References
ARAGORN ARAGORN detects tRNA and tmRNA in nucleotide sequences. tRNA tmRNA webserver source [128]
miReader miReader is a first of its type to detect mature miRNAs without any dependence upon 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. With miReader, one can now directly find out mature miRNAs from small RNA sequencing data, without any need of genomic/reference sequences. It has been developed for large number of Phyla and species, ranging from Vertebrate models to plant and fish models. Its accuracy has been found to be consistently >90% for large number of validatory testing. mature miRNA webserver/source webserver/source [129]
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 [130]
RISCbinder Prediction of guide strand of microRNAs. Mature miRNA webserver [131]
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 [132]
RNAmmer RNAmmer uses HMMER to annotate rRNA genes in genome sequences. Profiles were built using alignments from the European ribosomal RNA database[133] and the 5S Ribosomal RNA Database.[134] rRNA webserver source [135]
SnoReport Uses a combination 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 [136]
SnoScan Search for C/D box methylation guide snoRNA genes in a genomic sequence. C/D box snoRNA sourcecode, webserver [137][138]
tRNAscan-SE a program for the detection of transfer RNA genes in genomic sequence. tRNA sourcecode, webserver [138][139]
miRNAFold A fast ab initio software for searching for microRNA precursors in genomes. microRNA webserver [140]

RNA homology search software

Name Description Link References
ERPIN "Easy RNA Profile IdentificatioN" is an RNA motif search program reads a sequence alignement 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 [141][142][143]
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 [144][145][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. sourcecode [49]
PHMMTS "pair hidden Markov models on tree structures" is an extension of pair hidden Markov models defined on alignments of trees. sourcecode, webserver [147]
RaveNnA A slow and rigorous or fast and heuristic sequence-based filter for covariance models. sourcecode [148][149]
RSEARCH Takes a single RNA sequence with its secondary structure and utilizes a local alignment algorithm to search a database for homologous RNAs. sourcecode [150]
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 [151]

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 [152]
BRalibase II A benchmark of multiple sequence alignment programs upon structural RNAs no yes no data [153]
BRalibase 2.1 A benchmark of multiple sequence alignment programs upon structural RNAs no yes no data [154]
BRalibase III A critical assessment of the performance of homology search methods on noncoding RNA no yes no data [155]
CompaRNA An independent comparison of single-sequence and comparative methods for RNA secondary structure prediction yes no no AMU mirror or IIMCB mirror [156]
Notes
  1. Structure: benchmarks 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 Editingyesyes sourcecode [157]
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 [158]
Integrated Genome Browser (IGB) a multiple alignment viewer written in Java. yesno sourcecode [159]
Jalview a multiple alignment editor written in Java. yesno sourcecode [160][161]
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.yesyes sourcecode [162]
SARSE A graphical sequence editor for working with structural alignments of RNA.yesyes sourcecode [163]
Notes
  1. Alignment: view and edit an alignment, <yes|no>.
  2. Structure: view and edit structure, <yes|no>.

Inverse Folding/RNA design

Name Description Link References
Single state design
EteRNA/EteRNABot An RNA folding game that challenges players to come up with 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 [164]
RNAinverse The ViennaRNA package provides RNAinverse, an algorithm for designing sequences with desired structure. Web Server [14]
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 is also able to design interacting RNA molecules using RNAcofold of the ViennaRNA Package. A fully functional, earlier implementation using COMET is available. Web Server Source Code [165][166][167]
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 [168]
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 [169][170]
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 [171]
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 [172]
IncaRNAtion Successor of RNA-ensign that is able to specifically design sequences with a specified GC content using a GC-weighted Boltzmann ensemble and stochastic backtracking Source Code [173]
DSS-Opt The Dynamics in Sequence Space Optimization (DSS-Opt) approach uses Newtonian dynamics in the sequence space in combination with a negative design term and simulated annealing to optimize a sequence such that it folds into the desired secondary structure. Source Code [174]
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 [175][176]
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 sub-sequences (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 sub-sequences corresponding to the components. The major contributions of ERD are utilizing the natural RNA sequences, a different method for evaluating the sequences in each population, and a different hierarchical decomposition of the target structure into smaller sub-structures. Web Server Source Code [177]
antaRNA antaRNA uses an underlaying 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 as well as sequence domain specific definition of multiple GC values within one entity. Due to the flexible evaluation of the intermediate sequences using underlaying 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[178][179]
Dual state design
switch.pl The ViennaRNA package provides a Perl script to design RNA sequences that are able to 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 [180]
RiboMaker RiboMaker is 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 [181]
Multi state design
RNAdesign The underlying algorithm of RNAdesign is based on a combination of graph coloring and heuristic local optimization to find sequences that are able to adapt multiple prescribed conformations. In addition the software is also able make use of RNAcofold to design interacting RNA sequence pairs. Source Code [182]
Frnakenstein Frnakenstein applies a genetic algorithm to solve the inverse RNA folding problem. Source Code [183]
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. [Note 1] [184]
Notes
  1. Broken Link: Didn't find a functional link and contacted the authors (07/30/2014)

Secondary structure viewers/editors

Name Description Link References
PseudoViewer Automatically visualizing RNA pseudoknot structures as planar graphs. webapp/binary [185][186][187][188]
RNA Movies browse sequential paths through RNA secondary structure landscapes sourcecode [189][190]
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 [191]
RNA2D3D a program for generating, viewing, and comparing 3-dimensional models of RNA binary [192]
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 [193]
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 [194]
RILogo Visualizes the intra-/intermolecular base pairing of two interacting RNAs with sequence logos in a planar graph. web server / sourcecode [195]
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 [196]

See also

References

  1. Michiaki Hamada, Hisanori Kiryu, Kengo Sato, Toutai Mituyama, Kiyoshi Asai (2009). "Predictions of RNA secondary structure using generalized centroid estimators". Bioinformatics 25 (4): 465–473. doi:10.1093/bioinformatics/btn601. PMID 19095700.
  2. Michiaki Hamada, Hisanori Kiryu, Kengo Sato, Toutai Mituyama, Kiyoshi Asai (2009). "Predictions of RNA secondary structure by combining homologous sequence information". Bioinformatics 25 (12): i330 – i3388. doi:10.1093/bioinformatics/btp228. PMC 2687982. PMID 19478007.
  3. Shay Zakov, Yoav Goldberg, Michael Elhadad, Michal Ziv-Ukelson (2011). "Rich parameterization improves RNA structure prediction". Journal of Computational Biology 18 (11): 1525–1542. doi:10.1089/cmb.2011.0184. PMID 22035327.
  4. Do CB, Woods DA, Batzoglou S (2006). "CONTRAfold: RNA secondary structure prediction without physics-based models". Bioinformatics 22 (14): e90–8. doi:10.1093/bioinformatics/btl246. PMID 16873527.
  5. Bindewald E, Kluth T, Shapiro BA (2010). "CyloFold: secondary structure prediction including pseudoknots". Nucleic Acids Research 5 (341): 368–72. doi:10.1093/nar/gkq432. PMC 2896150. PMID 20501603.
  6. Swenson MS, Anderson J, Ash A, Gaurav P, Sükösd Z, Bader DA, Harvey SC, Heitsch CE. (2012). "GTfold: enabling parallel RNA secondary structure prediction on multi-core desktops.". BMC Res Notes 5: 341. doi:10.1186/1756-0500-5-341. PMC 3748833. PMID 22747589.
  7. Sato K, Kato Y, Hamada M, Akutsu T, Asai K (2011). "IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming". Bioinformatics 27 (13): i85–93. doi:10.1093/bioinformatics/btr215. PMC 3117384. PMID 21685106.
  8. Xayaphoummine A, Bucher T, Isambert H (2005). "Kinefold web server for RNA/DNA folding path and structure prediction including pseudoknots and knots". Nucleic Acids Res. 33 (Web Server issue): W605–10. doi:10.1093/nar/gki447. PMC 1160208. PMID 15980546.
  9. Xayaphoummine A, Bucher T, Thalmann F, Isambert H (2003). "Prediction and statistics of pseudoknots in RNA structures using exactly clustered stochastic simulations". Proc. Natl. Acad. Sci. U.S.A. 100 (26): 15310–5. arXiv:physics/0309117. Bibcode:2003PNAS..10015310X. doi:10.1073/pnas.2536430100. PMC 307563. PMID 14676318.
  10. 1 2 Zuker M, Stiegler P (1981). "Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information". Nucleic Acids Res. 9 (1): 133–48. doi:10.1093/nar/9.1.133. PMC 326673. PMID 6163133.
  11. Rivas E, Eddy SR (1999). "A dynamic programming algorithm for RNA structure prediction including pseudoknots". J. Mol. Biol. 285 (5): 2053–68. doi:10.1006/jmbi.1998.2436. PMID 9925784.
  12. Reeder J, Steffen P, Giegerich R (2007). "pknotsRG: RNA pseudoknot folding including near-optimal structures and sliding windows". Nucleic Acids Res. 35 (Web Server issue): W320–4. doi:10.1093/nar/gkm258. PMC 1933184. PMID 17478505.
  13. 1 2 Theis, Corinna and Janssen, Stefan and Giegerich, Robert (2010). "Prediction of RNA Secondary Structure Including Kissing Hairpin Motifs". In Moulton, Vincent and Singh, Mona. Algorithms in Bioinformatics (Lecture Notes in Computer Science ed.). Springer Berlin Heidelberg. pp. 52–64. doi:10.1007/978-3-642-15294-8_5. ISBN 978-3-642-15293-1.
  14. 1 2 3 4 5 6 7 I.L. Hofacker, W. Fontana, P.F. Stadler, S. Bonhoeffer, M. Tacker, P. Schuster (1994). "Fast Folding and Comparison of RNA Secondary Structures.". Monatshefte f. Chemie 125 (2): 167–188. doi:10.1007/BF00818163.
  15. McCaskill JS (1990). "The equilibrium partition function and base pair binding probabilities for RNA secondary structure". Biopolymers 29 (6-7): 1105–19. doi:10.1002/bip.360290621. PMID 1695107.
  16. Hofacker IL, Stadler PF (2006). "Memory efficient folding algorithms for circular RNA secondary structures". Bioinformatics 22 (10): 1172–6. doi:10.1093/bioinformatics/btl023. PMID 16452114.
  17. Bompfünewerer AF, Backofen R, Bernhart SH, et al. (2008). "Variations on RNA folding and alignment: lessons from Benasque". J Math Biol 56 (1-2): 129–144. doi:10.1007/s00285-007-0107-5. PMID 17611759.
  18. R. Giegerich, B.Voß, M. Rehmsmeier (2004). "Abstract shapes of RNA.". Nucleic Acids Res. 32 (16): 4843–4851. doi:10.1093/nar/gkh779. PMC 519098. PMID 15371549.
  19. B. Voß, R. Giegerich, M. Rehmsmeier (2006). "Complete probabilistic analysis of RNA shapes.". BMC Biology 4 (1): 5. doi:10.1186/1741-7007-4-5. PMC 1479382. PMID 16480488.
  20. D.H. Mathews, M.D. Disney, J. L. Childs, S.J. Schroeder, M. Zuker, D.H. Turner (2004). "Incorporating chemical modification constraints into a dynamic programming algorothm for prediction of RNA secondary structure.". Proceedings of the National Academy of Sciences of the United States of America 101 (19): 7287–7292. Bibcode:2004PNAS..101.7287M. doi:10.1073/pnas.0401799101. PMC 409911. PMID 15123812.
  21. D.H. Mathews (2004). "Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization.". RNA 10 (8): 1178–1190. doi:10.1261/rna.7650904. PMC 1370608. PMID 15272118.
  22. Tsang, Herbert H.; Wiese, Kay C. (2010). "SARNA-Predict: accuracy improvement of RNA secondary structure prediction using permutation-based simulated annealing.". IEEE/ACM Trans Comput Biol Bioinform. 7 (4): 727–740. doi:10.1109/TCBB.2008.97. PMID 21030739.
  23. Ding Y, Lawrence CE (2003). "A statistical sampling algorithm for RNA secondary structure prediction". Nucleic Acids Res. 31 (24): 7280–301. doi:10.1093/nar/gkg938. PMC 297010. PMID 14654704.
  24. Ding Y, Chan CY, Lawrence CE (2004). "Sfold web server for statistical folding and rational design of nucleic acids". Nucleic Acids Res. 32 (Web Server issue): W135–41. doi:10.1093/nar/gkh449. PMC 441587. PMID 15215366.
  25. Ding Y, Chan CY, Lawrence CE (2005). "RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble". RNA 11 (8): 1157–66. doi:10.1261/rna.2500605. PMC 1370799. PMID 16043502.
  26. Chan CY, Lawrence CE, Ding Y (2005). "Structure clustering features on the Sfold Web server". Bioinformatics 21 (20): 3926–8. doi:10.1093/bioinformatics/bti632. PMID 16109749.
  27. Markham NR, Zuker M (2008). "UNAFold: software for nucleic acid folding and hybridization.". Methods Mol Biol 453: 3–31. doi:10.1007/978-1-60327-429-6_1. PMID 18712296.
  28. 1 2 Schroeder S, Bleckley S, Stone JW (2011). "Ensemble of secondary structures for encapsidated satellite tobacco mosaic virus RNA consistent with chemical probing and crystallography constraints.". Biophysical Journal 101 (1): 167–175. Bibcode:2011BpJ...101..167S. doi:10.1016/j.bpj.2011.05.053. PMC 3127170. PMID 21723827.
  29. Frellsen J, Moltke I, Thiim M, Mardia KV, Ferkinghoff-Borg J, Hamelryck T (2009). Gardner, Paul, ed. "A probabilistic model of RNA conformational space.". PLoS Comput. Biol. 5 (6): e1000406. doi:10.1371/journal.pcbi.1000406. PMC 2691987. PMID 19543381.
  30. Das R, Baker D (September 2007). "Automated de novo prediction of native-like RNA tertiary structures". Proc. Natl. Acad. Sci. U.S.A. 104 (37): 14664–9. Bibcode:2007PNAS..10414664D. doi:10.1073/pnas.0703836104. PMC 1955458. PMID 17726102.
  31. Sharma S, Ding F, Dokholyan NV (September 2008). "iFoldRNA: three-dimensional RNA structure prediction and folding". Bioinformatics 24 (17): 1951–2. doi:10.1093/bioinformatics/btn328. PMC 2559968. PMID 18579566.
  32. Parisien M, Major F (2008). "The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data". Nature 452 (1): 51–55. Bibcode:2008Natur.452...51P. doi:10.1038/nature06684. PMID 18322526.
  33. SC Flores, RB Altman (September 2010). "Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters". RNA 15 (9): 1769–1778. doi:10.1261/rna.1270809. PMC 2648710. PMID 20651028.
  34. Jonikas MA, Radmer RJ, Laederach A, et al. (February 2009). "Turning limited experimental information into 3D models of RNA". RNA 16 (2): 189–99. doi:10.1261/rna.2112110. PMC 2924536. PMID 19144906.
  35. Popenda M, Szachniuk M, Antczak M, Purzycka KJ, Lukasiak P, Bartol N, Blazewicz J, Adamiak RW (2012). "Automated 3D structure composition for large RNAs". Nucleic Acids Res. 40 (14): 1–12. doi:10.1093/nar/gks339. PMC 3413140. PMID 22539264.
  36. Perriquet O, Touzet H, Dauchet M. (2003). "Finding the common structure shared by two homologous RNAs.". Bioinformatics. 19 (1): 108–16. doi:10.1093/bioinformatics/19.1.108. PMID 12499300.
  37. Touzet H, Perriquet O. (Jul 1, 2004). "CARNAC: folding families of related RNAs.". Nucleic Acids Res. 32. (Web Server issue) (Web Server issue): W142–5. doi:10.1093/nar/gkh415. PMC 441553. PMID 15215367.
  38. Michiaki Hamada, Kengo Sato, Kiyoshi Asai (2011). "Improving the accuracy of predicting secondary structure for aligned RNA sequences". Nucleic Acids Res. 39 (2): 393–402. doi:10.1093/nar/gkq792. PMC 3025558. PMID 20843778.
  39. Michiaki Hamada, Kengo Sato, Hisanori Kiryu, Toutai Mituyama, Kiyoshi Asai (2009). "CentroidAlign: fast and accurate aligner for structured RNAs by maximizing expected sum-of-pairs score". Bioinformatics 25 (24): 3236–43. doi:10.1093/bioinformatics/btp580. PMID 19808876.
  40. Yao Z, Weinberg Z, Ruzzo WL (2006). "CMfinder--a covariance model based RNA motif finding algorithm". Bioinformatics 22 (4): 445–52. doi:10.1093/bioinformatics/btk008. PMID 16357030.
  41. Dowell RD, Eddy SR (2006). "Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints". BMC Bioinformatics 7 (1): 400. doi:10.1186/1471-2105-7-400. PMC 1579236. PMID 16952317.
  42. Sato K, Kato Y, Akutsu T, Asai K, Sakakibara Y (2012). "DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition". Bioinformatics 28 (24): 3218–24. doi:10.1093/bioinformatics/bts612. PMID 23060618.
  43. Mathews DH, Turner DH (2002). "Dynalign: an algorithm for finding the secondary structure common to two RNA sequences". J. Mol. Biol. 317 (2): 191–203. doi:10.1006/jmbi.2001.5351. PMID 11902836.
  44. Mathews DH (2005). "Predicting a set of minimal free energy RNA secondary structures common to two sequences". Bioinformatics 21 (10): 2246–53. doi:10.1093/bioinformatics/bti349. PMID 15731207.
  45. Harmanci AO, Sharma G, Mathews DH (2007). "Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign". BMC Bioinformatics 8 (1): 130. doi:10.1186/1471-2105-8-130. PMC 1868766. PMID 17445273.
  46. Torarinsson E, Havgaard JH, Gorodkin J (2007). "Multiple structural alignment and clustering of RNA sequences". Bioinformatics 23 (8): 926–32. doi:10.1093/bioinformatics/btm049. PMID 17324941.
  47. Milo Nimrod, Zakov Shay, Katzenelson Erez, Bachmat Eitan, Dinitz Yefim, Ziv-Ukelson Michal (2012). "RNA Tree Comparisons via Unrooted Unordered Alignments". Algorithms in Bioinformatics 7534: 135–148. doi:10.1007/978-3-642-33122-0_11.
  48. Milo Nimrod, Zakov Shay, Katzenelson Erez, Bachmat Eitan, Dinitz Yefim, Ziv-Ukelson Michal (2013). "Unrooted unordered homeomorphic subtree alignment of RNA trees". Algorithms for Molecular Biology 8 (1): 13. doi:10.1186/1748-7188-8-13. ISSN 1748-7188. PMID 23590940.
  49. 1 2 3 Heyne S, Costa F, Rose D, Backofen R (2012). "GraphClust: alignment-free structural clustering of local RNA secondary structures". Bioinformatics 28 (12): i224–i232. doi:10.1093/bioinformatics/bts224. PMC 3371856. PMID 22689765.
  50. Bindewald E, Shapiro BA (2006). "RNA secondary structure prediction from sequence alignments using a network of k-nearest neighbor classifiers". RNA 12 (3): 342–52. doi:10.1261/rna.2164906. PMC 1383574. PMID 16495232.
  51. Bauer M, Klau GW, Reinert K. (2007). "Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization.". BMC Bioinformatics. 8 (1): 271. doi:10.1186/1471-2105-8-271. PMC 1955456. PMID 17662141.
  52. Will S, Reiche K, Hofacker IL, Stadler PF, Backofen R (2007). "Inferring noncoding RNA families and classes by means of genome-scale structure-based clustering.". PLoS Comput. Biol. 3 (4): e65. Bibcode:2007PLSCB...3...65W. doi:10.1371/journal.pcbi.0030065. PMC 1851984. PMID 17432929.
  53. Lindgreen S, Gardner PP, Krogh A (2006). "Measuring covariation in RNA alignments: physical realism improves information measures". Bioinformatics 22 (24): 2988–95. doi:10.1093/bioinformatics/btl514. PMID 17038338.
  54. Lindgreen S, Gardner PP, Krogh A (2007). "MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing". Bioinformatics 23 (24): 3304–11. doi:10.1093/bioinformatics/btm525. PMID 18006551.
  55. Xu Z, Mathews DH (2011). "Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequences". Bioinformatics 27 (5): 626–632. doi:10.1093/bioinformatics/btq726. PMC 3042186. PMID 21193521.
  56. Kiryu H, Tabei Y, Kin T, Asai K (2007). "Murlet: a practical multiple alignment tool for structural RNA sequences". Bioinformatics 23 (13): 1588–98. doi:10.1093/bioinformatics/btm146. PMID 17459961.
  57. Tabei Y, Kiryu H, Kin T, Asai K (2008). "A fast structural multiple alignment method for long RNA sequences". BMC Bioinformatics 33 (1): 33. doi:10.1186/1471-2105-9-33.
  58. Harmanci AO, Sharma G, Mathews DH (2008). "PARTS: probabilistic alignment for RNA joinT secondary structure prediction.". Nucleic Acids Res 36 (7): 2406–17. doi:10.1093/nar/gkn043. PMC 2367733. PMID 18304945.
  59. Knudsen B, Hein J (1999). "RNA secondary structure prediction using stochastic context-free grammars and evolutionary history". Bioinformatics 15 (6): 446–54. doi:10.1093/bioinformatics/15.6.446. PMID 10383470.
  60. Knudsen B, Hein J (2003). "Pfold: RNA secondary structure prediction using stochastic context-free grammars". Nucleic Acids Res. 31 (13): 3423–8. doi:10.1093/nar/gkg614. PMC 169020. PMID 12824339.
  61. Seemann S E, Gorodkin J, Backofen R (2008). "Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments". Nucleic Acids Res. 36 (20): 6355–62. doi:10.1093/nar/gkn544. PMC 2582601. PMID 18836192.
  62. Doose G, Metzler D (2012). "Bayesian sampling of evolutionarily conserved RNA secondary structures with pseudoknots.". Bioinformatics 28 (17): 2242–2248. doi:10.1093/bioinformatics/bts369. PMID 22796961.
  63. Hofacker IL, Bernhart SH, Stadler PF (2004). "Alignment of RNA base pairing probability matrices". Bioinformatics 20 (14): 2222–7. doi:10.1093/bioinformatics/bth229. PMID 15073017.
  64. Wei D, Alpert LV, Lawrence CE (2011). "RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequence". Bioinformatics 27 (18): 2486–2493. doi:10.1093/bioinformatics/btr421. PMC 3167047. PMID 21788211.
  65. Wilm A, Higgins DG, Notredame C (May 2008). "R-Coffee: a method for multiple alignment of non-coding RNA". Nucleic Acids Res. 36 (9): e52. doi:10.1093/nar/gkn174. PMC 2396437. PMID 18420654.
  66. Moretti S, Wilm A, Higgins DG, Xenarios I, Notredame C (July 2008). "R-Coffee: a web server for accurately aligning noncoding RNA sequences". Nucleic Acids Res. 36 (Web Server issue): W10–3. doi:10.1093/nar/gkn278. PMC 2447777. PMID 18483080.
  67. Harmanci AO, Sharma G, Mathews DH (2011). "TurboFold: iterative probabilistic estimation of secondary structures for multiple RNA sequence". BMC Bioinformatics 12 (1): 108. doi:10.1186/1471-2105-12-108. PMC 3120699. PMID 21507242.
  68. Seetin MG, Mathews DH (2012). "TurboKnot: rapid prediction of conserved RNA secondary structures including pseudoknots". Bioinformatics 28 (6): 792–798. doi:10.1093/bioinformatics/bts044. PMC 3307117. PMID 22285566.
  69. Hofacker IL, Fekete M, Stadler PF (2002). "Secondary structure prediction for aligned RNA sequences". J. Mol. Biol. 319 (5): 1059–66. doi:10.1016/S0022-2836(02)00308-X. PMID 12079347.
  70. Voß, Björn (2006). "Structural analysis of aligned RNAs". Nucleic Acids Research 34 (19): 5471–5481. doi:10.1093/nar/gkl692. PMC 1636479. PMID 17020924.
  71. Reeder J, Giegerich R (2005). "Consensus shapes: an alternative to the Sankoff algorithm for RNA consensus structure prediction". Bioinformatics 21 (17): 3516–23. doi:10.1093/bioinformatics/bti577. PMID 16020472.
  72. Höchsmann M, Töller T, Giegerich R, Kurtz S (2003). "Local similarity in RNA secondary structures". Proc IEEE Comput Soc Bioinform Conf 2: 159–68. PMID 16452790.
  73. Höchsmann M, Voss B, Giegerich R (2004). "Pure multiple RNA secondary structure alignments: a progressive profile approach". IEEE/ACM Trans Comput Biol Bioinform 1 (1): 53–62. doi:10.1109/TCBB.2004.11. PMID 17048408.
  74. Hamada M, Tsuda K, Kudo T, Kin T, Asai K (2006). "Mining frequent stem patterns from unaligned RNA sequences". Bioinformatics 22 (20): 2480–7. doi:10.1093/bioinformatics/btl431. PMID 16908501.
  75. Xu X, Ji Y, Stormo GD (2007). "RNA Sampler: a new sampling based algorithm for common RNA secondary structure prediction and structural alignment". Bioinformatics 23 (15): 1883–91. doi:10.1093/bioinformatics/btm272. PMID 17537756.
  76. Tabei Y, Tsuda K, Kin T, Asai K (2006). "SCARNA: fast and accurate structural alignment of RNA sequences by matching fixed-length stem fragments". Bioinformatics 22 (14): 1723–9. doi:10.1093/bioinformatics/btl177. PMID 16690634.
  77. Meyer IM, Miklós I (2007). "SimulFold: simultaneously inferring RNA structures including pseudoknots, alignments, and trees using a Bayesian MCMC framework". PLoS Comput. Biol. 3 (8): e149. Bibcode:2007PLSCB...3..149M. doi:10.1371/journal.pcbi.0030149. PMC 1941756. PMID 17696604.
  78. Holmes I (2005). "Accelerated probabilistic inference of RNA structure evolution". BMC Bioinformatics 6 (1): 73. doi:10.1186/1471-2105-6-73. PMC 1090553. PMID 15790387.
  79. Dalli D, Wilm A, Mainz I, Steger G (2006). "STRAL: progressive alignment of non-coding RNA using base pairing probability vectors in quadratic time". Bioinformatics 22 (13): 1593–9. doi:10.1093/bioinformatics/btl142. PMID 16613908.
  80. Engelen S, Tahi F (2010). "Tfold: efficient in silico prediction of non-coding RNA secondary structures". Nucleic Acids Res. 7 (38): 2453–66. doi:10.1093/nar/gkp1067. PMC 2853104. PMID 20047957.
  81. Torarinsson E, Lindgreen S (2008). "WAR: Webserver for aligning structural RNAs.". Nucleic Acids Res 36 (Web Server issue): W79–84. doi:10.1093/nar/gkn275. PMC 2447782. PMID 18492721.
  82. 1 2 Klosterman P; Uzilov, AV; Bendaña, YR; Bradley, RK; Chao, S; Kosiol, C; Goldman, N; Holmes, I (2006). "XRate: a fast prototyping, training and annotation tool for phylo-grammars". BMC Bioinformatics 7 (1): 428. doi:10.1186/1471-2105-7-428. PMC 1622757. PMID 17018148.
  83. Eggenhofer, Tafer, Stadler, Hofacker (2011). "RNApredator: fast accessibility-based prediction of sRNA targets.". Nucleic Acids Res. 39 (suppl 2: W149-W154): W149–W154. doi:10.1093/nar/gkr467. PMC 3125805. PMID 21672960.
  84. Gerlach W, Giegerich R (2006). "GUUGle: a utility for fast exact matching under RNA complementary rules including G-U base pairing.". Bioinformatics 22 (6): 762–764. doi:10.1093/bioinformatics/btk041. PMID 16403789.
  85. 1 2 Wright PR, Georg J, Mann M, Sorescu DA, Richter AS, Lott S, Kleinkauf R, Hess WR, Backofen R (2014). "CopraRNA and IntaRNA: predicting small RNA targets, networks and interaction domains.". Nucleic Acids Res 42 (Web Server): W119–23. doi:10.1093/nar/gku359. PMID 24838564.
  86. Busch A, Richter AS, Backofen R (2008). "IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions.". Bioinformatics 24 (24): 2849–56. doi:10.1093/bioinformatics/btn544. PMC 2639303. PMID 18940824.
  87. Richter AS, Schleberger C, Backofen R, Steglich C (2010). "Seed-based INTARNA prediction combined with GFP-reporter system identifies mRNA targets of the small RNA Yfr1.". Bioinformatics 26 (1): 1–5. doi:10.1093/bioinformatics/btp609. PMC 2796815. PMID 19850757.
  88. Smith C, Heyne S, Richter AS, Will S, Backofen R (2010). "Freiburg RNA Tools: a web server integrating INTARNA, EXPARNA and LOCARNA.". Nucleic Acids Res. 38. Suppl (Web Server): W373–7. doi:10.1093/nar/gkq316. PMC 2896085. PMID 20444875.
  89. Wright PR, Richter AS, Papenfort K, Mann M, Vogel J, Hess WR, Backofen R, Georg J (2013). "Comparative genomics boosts target prediction for bacterial small RNAs.". Proc Natl Acad Sci U S A 110 (37): E3487–E3496. doi:10.1073/pnas.1303248110. PMC 3773804. PMID 23980183.
  90. Górska A, Jasiński M, Trylska J (2015). "MINT: software to identify motifs and short-range interactions in trajectories of nucleic acids.". Nucleic Acids Research 43 (17): e114. doi:10.1093/nar/gkv559. PMID 26024667.
  91. R.M. Dirks, J.S. Bois, J.M. Schaeffer, E. Winfree, N.A. Pierce (2007). "Thermodynamic Analysis of Interacting Nucleic Acid Strands". SIAM Review 49 (1): 65–88. Bibcode:2007SIAMR..49...65D. doi:10.1137/060651100.
  92. D.H. Mathews, M.E. Burkard, S.M. Freier, D.H. Turner (1999). "Predicting Oligonucleotide Affinity to RNA Targets.". RNA 5 (11): 1458–1469. doi:10.1017/S1355838299991148. PMC 1369867. PMID 10580474.
  93. H. Chitsaz, R. Salari, S.C. Sahinalp, R. Backofen (2009). "A Partition Function Algorithm for Interacting Nucleic Acid Strands.". Bioinformatics 25 (12): i365–i373. doi:10.1093/bioinformatics/btp212. PMC 2687966. PMID 19478011.
  94. Andrew Xiang Li, Jing Qin, Manja Marz, Christian M. Reidys (2011). "RNA–RNA interaction prediction based on multiple sequence alignments.". Bioinformatics 27 (4): 456–463. doi:10.1093/bioinformatics/btq659.
  95. Kato Y, Sato K, Hamada M, Watanabe Y, Asai K, Akutsu T (2010). "RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming". Bioinformatics 26 (18): i460–6. doi:10.1093/bioinformatics/btq372. PMC 2935440. PMID 20823308.
  96. Bernhart SH, Tafer H, Mückstein U, Flamm C, Stadler PF, Hofacker IL (2006). "Partition function and base pairing probabilities of RNA heterodimers". Algorithms Mol Biol 1 (1): 3. doi:10.1186/1748-7188-1-3. PMC 1459172. PMID 16722605.
  97. 1 2 3 Rehmsmeier M, Steffen P, Hochsmann M, Giegerich R (2004). "Fast and effective prediction of microRNA/target duplexes". RNA 10 (10): 1507–17. doi:10.1261/rna.5248604. PMC 1370637. PMID 15383676.
  98. 1 2 3 Krüger J, Rehmsmeier M (2006). "RNAhybrid: microRNA target prediction easy, fast and flexible". Nucleic Acids Res. 34 (Web Server issue): W451–4. doi:10.1093/nar/gkl243. PMC 1538877. PMID 16845047.
  99. Mückstein U, Tafer H, Hackermüller J, Bernhart SH, Stadler PF, Hofacker IL (2006). "Thermodynamics of RNA-RNA binding". Bioinformatics 22 (10): 1177–82. doi:10.1093/bioinformatics/btl024. PMID 16446276.
  100. 1 2 Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, Lim B, Rigoutsos I (2006). "A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes.". Cell 126 (6): 1203–17. doi:10.1016/j.cell.2006.07.031. PMID 16990141.
  101. Baek D, Villén J, Shin C, Camargo FD, Gygi SP, Bartel DP (2008). "The impact of microRNAs on protein output.". Nature 455 (7209): 64–71. doi:10.1038/nature07242. PMC 2745094. PMID 18668037.
  102. Alexiou P, Maragkakis M, Papadopoulos GL, Reczko M, Hatzigeorgiou AG (2009). "Lost in translation: an assessment and perspective for computational microRNA target identification.". Bioinformatics 25 (23): 3049–55. doi:10.1093/bioinformatics/btp565. PMID 19789267.
  103. Ritchie W, Flamant S, Rasko JE. (2009). "Predicting microRNA targets and functions: traps for the unwary". Nature Methods 6 (6): 3978–398. doi:10.1038/nmeth0609-397. PMID 19478799.
  104. Chiu, Hua-Sheng; Llobet-Navas, David; Yang, Xuerui; Chung, Wei-Jen; Ambesi-Impiombato, Alberto; Iyer, Archana; Kim, Hyunjae "Ryan"; Seviour, Elena G.; Luo, Zijun; Sehgal, Vasudha; Moss, Tyler; Lu, Yiling; Ram, Prahlad; Silva, José; Mills, Gordon B.; Califano, Andrea; Sumazin, Pavel (February 2015). "Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks". Genome Research 25 (2): 257–67. doi:10.1101/gr.178194.114. PMID 25378249.
  105. 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 (2009). "Accurate microRNA target prediction correlates with protein repression levels.". BMC Bioinformatics 10 (1): 295. doi:10.1186/1471-2105-10-295. PMC 2752464. PMID 19765283.
  106. Thadani R, Tammi MT (2006). "MicroTar: predicting microRNA targets from RNA duplexes.". BMC Bioinformatics. 7. Suppl 5 (Suppl 5): S20. doi:10.1186/1471-2105-7-S5-S20. PMC 1764477. PMID 17254305.
  107. Kim SK, Nam JW, Rhee JK, Lee WJ, Zhang BT (2006). "miTarget: microRNA target gene prediction using a support vector machine.". BMC Bioinformatics 7 (1): 411. doi:10.1186/1471-2105-7-411. PMC 1594580. PMID 16978421.
  108. Friedman, Y.; Naamati, G.; Linial, M. (2010). "MiRror: A combinatorial analysis web tool for ensembles of microRNAs and their targets". Bioinformatics 26 (15): 1920–1921. doi:10.1093/bioinformatics/btq298. PMID 20529892.
  109. Balaga, O.; Friedman, Y.; Linial, M. (2012). "Toward a combinatorial nature of microRNA regulation in human cells". Nucleic Acids Research 40 (19): 9404–9416. doi:10.1093/nar/gks759. PMC 3479204. PMID 22904063.
  110. Krek A, Grün D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, Rajewsky N (2005). "Combinatorial microRNA target predictions.". Nat Genet 37 (5): 495–500. doi:10.1038/ng1536. PMID 15806104.
  111. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E (2007). "The role of site accessibility in microRNA target recognition.". Nat Genet 39 (10): 1278–84. doi:10.1038/ng2135. PMID 17893677.
  112. van Dongen S, Abreu-Goodger C, Enright AJ (2008). "Detecting microRNA binding and siRNA off-target effects from expression data.". Nat Methods 5 (12): 1023–5. doi:10.1038/nmeth.1267. PMC 2635553. PMID 18978784.
  113. Bartonicek N, Enright AJ (2010). "SylArray: A web-server for automated detection of miRNA effects from expression data.". Bioinformatics 26 (22): 2900–1. doi:10.1093/bioinformatics/btq545. PMID 20871108.
  114. R. Heikham and R. Shankar (2010). "Flanking region sequence information to refine microRNA target predictions.". Journal of Biosciences 35 (1): 105–18. doi:10.1007/s12038-010-0013-7. PMID 20413915.
  115. Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB (2003). "Prediction of mammalian microRNA targets.". Cell 115 (7): 787–98. doi:10.1016/S0092-8674(03)01018-3. PMID 14697198.
  116. Lewis BP, Burge CB, Bartel DP (2005). "Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.". Cell 120 (1): 15–20. doi:10.1016/j.cell.2004.12.035. PMID 15652477.
  117. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP (2007). "MicroRNA targeting specificity in mammals: determinants beyond seed pairing.". Mol Cell 27 (1): 91–105. doi:10.1016/j.molcel.2007.06.017. PMC 3800283. PMID 17612493.
  118. Garcia DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP (2011). "Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs.". Nature Structural & Molecular Biology 18 (10): 1139–1146. doi:10.1038/nsmb.2115. PMC 3190056. PMID 21909094.
  119. Agarwal, Vikram; Bell, George W.; Nam, Jin-Wu; Bartel, David P. (2015-08-12). "Predicting effective microRNA target sites in mammalian mRNAs". eLife 4: e05005. doi:10.7554/eLife.05005. ISSN 2050-084X. PMC 4532895. PMID 26267216.
  120. Washietl S, Hofacker IL (2004). "Consensus folding of aligned sequences as a new measure for the detection of functional RNAs by comparative genomics". J. Mol. Biol. 342 (1): 19–30. doi:10.1016/j.jmb.2004.07.018. PMID 15313604.
  121. Pedersen JS, Bejerano G, Siepel A, et al. (2006). "Identification and classification of conserved RNA secondary structures in the human genome". PLoS Comput. Biol. 2 (4): e33. Bibcode:2006PLSCB...2...33P. doi:10.1371/journal.pcbi.0020033. PMC 1440920. PMID 16628248.
  122. Coventry A, Kleitman DJ, Berger BA (2004). "MSARI: Multiple sequence alignments for statistical detection of RNA secondary structure". PNAS 101 (33): 12102–12107. Bibcode:2004PNAS..10112102C. doi:10.1073/pnas.0404193101. PMC 514400. PMID 15304649.
  123. Rivas E, Eddy SR (2001). "Noncoding RNA gene detection using comparative sequence analysis". BMC Bioinformatics 2 (1): 8. doi:10.1186/1471-2105-2-8. PMC 64605. PMID 11801179.
  124. Rivas E, Klein RJ, Jones TA, Eddy SR (2001). "Computational identification of noncoding RNAs in E. coli by comparative genomics". Curr. Biol. 11 (17): 1369–73. doi:10.1016/S0960-9822(01)00401-8. PMID 11553332.
  125. Washietl S, Hofacker IL, Stadler PF (2005). "Fast and reliable prediction of noncoding RNAs". Proc. Natl. Acad. Sci. U.S.A. 102 (7): 2454–9. Bibcode:2005PNAS..102.2454W. doi:10.1073/pnas.0409169102. PMC 548974. PMID 15665081.
  126. Gruber AR, Neuböck R, Hofacker IL, Washietl S (2007). "The RNAz web server: prediction of thermodynamically stable and evolutionarily conserved RNA structures". Nucleic Acids Res. 35 (Web Server issue): W335–8. doi:10.1093/nar/gkm222. PMC 1933143. PMID 17452347.
  127. Washietl S (2007). "Prediction of Structural Noncoding RNAs With RNAz". Methods Mol. Biol. 395: 503–26. doi:10.1007/978-1-59745-514-5_32. PMID 17993695.
  128. Laslett D, Canback B (2004). "ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences.". Nucl. Acids Res. 32 (1): 39. doi:10.1093/nar/gkh152. PMC 373265. PMID 14704338.
  129. Jha A, Shankar R (2013). "miReader: Discovering novel miRNAs in species without sequenced genome.". PLOS ONE 8 (6): e66857. doi:10.1371/journal.pone.0066857. PMC 3689854. PMID 23805282.
  130. Artzi S, Kiezun A, Shomron N (2008). "miRNAminer: a tool for homologous microRNA gene search.". BMC Bioinformatics 9 (1): 39. doi:10.1186/1471-2105-9-39. PMC 2258288. PMID 18215311.
  131. Ahmed F, Ansari HR and Raghava GPS (2009). "Prediction of guide strand of microRNAs from its sequence and secondary structure". BMC Bioinformatics 10 (1): 105. doi:10.1186/1471-2105-10-105.
  132. Hertel J, Stadler PF (2006). "Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data.". Bioinformatics 22 (14): e197–202. doi:10.1093/bioinformatics/btl257. PMID 16873472.
  133. Wuyts J, Perrière G, Van De Peer Y (2004). "The European ribosomal RNA database.". Nucleic Acids Res 32 (Database issue): D101–3. doi:10.1093/nar/gkh065. PMC 308799. PMID 14681368.
  134. Szymanski M, Barciszewska MZ, Erdmann VA, Barciszewski J (2002). "5S Ribosomal RNA Database.". Nucleic Acids Res 30 (1): 176–8. doi:10.1093/nar/30.1.176. PMC 99124. PMID 11752286.
  135. Lagesen K, Hallin P, Rødland EA, Staerfeldt HH, Rognes T, Ussery DW (2007). "RNAmmer: consistent and rapid annotation of ribosomal RNA genes.". Nucleic Acids Res 35 (9): 3100–8. doi:10.1093/nar/gkm160. PMC 1888812. PMID 17452365.
  136. Hertel J, Hofacker IL, Stadler PF (2008). "SnoReport: computational identification of snoRNAs with unknown targets.". Bioinformatics 24 (2): 158–64. doi:10.1093/bioinformatics/btm464. PMID 17895272.
  137. Lowe, T. M.; Eddy, S. R. (February 1999). "A Computational Screen for Methylation Guide snoRNAs in Yeast". Science 283 (5405): 1168–1171. Bibcode:1999Sci...283.1168L. doi:10.1126/science.283.5405.1168. PMID 10024243.
  138. 1 2 Schattner P, Brooks AN, Lowe TM (2005). "The tRNAscan-SE, snoscan and snoGPS web servers for the detection of tRNAs and snoRNAs.". Nucleic Acids Res 33 (Web Server issue): W686–9. doi:10.1093/nar/gki366. PMC 1160127. PMID 15980563.
  139. Lowe TM, Eddy SR (1997). "tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.". Nucleic Acids Res 25 (5): 955–64. doi:10.1093/nar/25.5.955. PMC 146525. PMID 9023104.
  140. Tempel S, Tahi F (2012). "A fast ab-initio method for predicting miRNA precursors in genomes.". Nucleic Acids Res. 40 (11): 955–64. doi:10.1093/nar/gks146. PMC 3367186. PMID 22362754.
  141. Gautheret D, Lambert A (2001). "Direct RNA motif definition and identification from multiple sequence alignments using secondary structure profiles.". J Mol Biol 313 (5): 1003–11. doi:10.1006/jmbi.2001.5102. PMID 11700055.
  142. Lambert A, Fontaine JF, Legendre M, Leclerc F, Permal E, Major F, Putzer H, Delfour O, Michot B, Gautheret D (2004). "The ERPIN server: an interface to profile-based RNA motif identification.". Nucleic Acids Res 32 (Web Server issue): W160–5. doi:10.1093/nar/gkh418. PMC 441556. PMID 15215371.
  143. Lambert A, Legendre M, Fontaine JF, Gautheret D (2005). "Computing expectation values for RNA motifs using discrete convolutions.". BMC Bioinformatics 6 (1): 118. doi:10.1186/1471-2105-6-118. PMC 1168889. PMID 15892887.
  144. Nawrocki EP, Eddy SR (2007). "Query-dependent banding (QDB) for faster RNA similarity searches.". PLoS Comput. Biol. 3 (3): e56. Bibcode:2007PLSCB...3...56N. doi:10.1371/journal.pcbi.0030056. PMC 1847999. PMID 17397253.
  145. Eddy SR (2002). "A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure.". BMC Bioinformatics 3 (1): 18. doi:10.1186/1471-2105-3-18. PMC 119854. PMID 12095421.
  146. Eddy SR, Durbin R (1994). "RNA sequence analysis using covariance models.". Nucleic Acids Res 22 (11): 2079–88. doi:10.1093/nar/22.11.2079. PMC 308124. PMID 8029015.
  147. Sato K, Sakakibara Y (2005). "RNA secondary structural alignment with conditional random fields.". Bioinformatics. 21. Suppl 2 (suppl_2): ii237–42. doi:10.1093/bioinformatics/bti1139. PMID 16204111.
  148. Weinberg Z, Ruzzo WL (2004). "Exploiting conserved structure for faster annotation of non-coding RNAs without loss of accuracy.". Bioinformatics. 20. Suppl 1 (suppl_1): i334–41. doi:10.1093/bioinformatics/bth925. PMID 15262817.
  149. Weinberg Z, Ruzzo WL (2006). "Sequence-based heuristics for faster annotation of non-coding RNA families.". Bioinformatics 22 (1): 35–9. doi:10.1093/bioinformatics/bti743. PMID 16267089.
  150. Klein RJ, Eddy SR (2003). "RSEARCH: finding homologs of single structured RNA sequences.". BMC Bioinformatics 4 (1): 44. doi:10.1186/1471-2105-4-44. PMC 239859. PMID 14499004.
  151. Meyer F, Kurtz S, Backofen R, Will S, Beckstette M (2011). "Structator: fast index-based search for RNA sequence-structure patterns". BMC Bioinformatics 12 (1): 214. doi:10.1186/1471-2105-12-214. PMC 3154205. PMID 21619640.
  152. Gardner PP, Giegerich R (2004). "A comprehensive comparison of comparative RNA structure prediction approaches". BMC Bioinformatics 5 (1): 140. doi:10.1186/1471-2105-5-140. PMC 526219. PMID 15458580.
  153. Gardner PP, Wilm A, Washietl S (2005). "A benchmark of multiple sequence alignment programs upon structural RNAs". Nucleic Acids Res. 33 (8): 2433–9. doi:10.1093/nar/gki541. PMC 1087786. PMID 15860779.
  154. Wilm A, Mainz I, Steger G (2006). "An enhanced RNA alignment benchmark for sequence alignment programs.". Algorithms Mol Biol 1 (1): 19. doi:10.1186/1748-7188-1-19. PMC 1635699. PMID 17062125.
  155. Freyhult EK, Bollback JP, Gardner PP (2007). "Exploring genomic dark matter: a critical assessment of the performance of homology search methods on noncoding RNA". Genome Res. 17 (1): 117–25. doi:10.1101/gr.5890907. PMC 1716261. PMID 17151342.
  156. Puton T, Kozlowski LP, Rother KM, Bujnicki JM (2013). "CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction". Nucleic Acids Research 41 (7): 4307–23. doi:10.1093/nar/gkt101. PMID 23435231.
  157. Seibel PN, Müller T, Dandekar T, Schultz J, Wolf M (2006). "4SALE--a tool for synchronous RNA sequence and secondary structure alignment and editing". BMC Bioinformatics 7 (1): 498. doi:10.1186/1471-2105-7-498. PMC 1637121. PMID 17101042.
  158. Bendana YR, Holmes IH (2008). "Colorstock, SScolor, Rat ́on: RNA Alignment Visualization Tools". Bioinformatics 24 (4): 579–80. doi:10.1093/bioinformatics/btm635. PMID 18218657.
  159. Nicol JW, Helt GA, Blanchard SG Jr, Raja A, Loraine AE (2009). "The Integrated Genome Browser: Free software for distribution and exploration of genome-scale data sets.". Bioinformatics 25 (20): 2730–2731. doi:10.1093/bioinformatics/btp472. PMC 2759552. PMID 19654113.
  160. Waterhouse AM, Procter JB, Martin DM, Clamp M, Barton GJ (2009). "Jalview Version 2--a multiple sequence alignment editor and analysis workbench.". Bioinformatics 25 (9): 1189–91. doi:10.1093/bioinformatics/btp033. PMC 2672624. PMID 19151095.
  161. Clamp M, Cuff J, Searle SM, Barton GJ (2004). "The Jalview Java alignment editor.". Bioinformatics 20 (3): 426–7. doi:10.1093/bioinformatics/btg430. PMID 14960472.
  162. Griffiths-Jones S (2005). "RALEE--RNA ALignment editor in Emacs". Bioinformatics 21 (2): 257–9. doi:10.1093/bioinformatics/bth489. PMID 15377506.
  163. Andersen ES, Lind-Thomsen A, Knudsen B, et al. (2007). "Semiautomated improvement of RNA alignments". RNA 13 (11): 1850–9. doi:10.1261/rna.215407. PMC 2040093. PMID 17804647.
  164. Lee, J. and Kladwang, W. and Lee, M. and Cantu, D. and Azizyan, M. and Kim, H. and Limpaecher, A. and Yoon, S. and Treuille, A. and Das, R. (2014). "RNA design rules from a massive open laboratory". PNAS 111 (6): 2122–2127. doi:10.1073/pnas.1313039111. line feed character in |author= at position 67 (help)
  165. J. A. Garcia-Martin, P. Clote, I. Dotu (2013). "RNAiFold: A constraint programming algorithm for RNA inverse folding and molecular design". Journal of Bioinformatics and Computational Biology 11 (2): 1350001. doi:10.1142/S0219720013500017. PMID 23600819.
  166. J. A. Garcia-Martin, P. Clote, I. Dotu (2013). "RNAiFold: a web server for RNA inverse folding and molecular design". Nucleic Acids Research 41 (W1): W465-W470. doi:10.1093/nar/gkt280. PMC 3692061. PMID 23700314.
  167. J. A. Garcia-Martin, I. Dotu, P. Clote (2015). "RNAiFold 2.0: a web server and software to design custom and Rfam-based RNA molecules". Nucleic Acids Research 43: W513–21. doi:10.1093/nar/gkv460. PMID 26019176.
  168. M Andronescu, A P Fejes, F Hutter, H H Hoos and A Condon (2004). "A new algorithm for RNA secondary structure design". Journal of Molecular Biology 336 (3): 607–624. doi:10.1016/j.jmb.2003.12.041. PMID 15095976.
  169. A Busch and R Backofen (2006). "INFO-RNA--a fast approach to inverse RNA folding". Bioinformatics 22 (15): 1823–1831. doi:10.1093/bioinformatics/btl194. PMID 16709587.
  170. A Busch and R Backofen (2007). "INFO-RNA--a server for fast inverse RNA folding satisfying sequence constraints". Nucleic Acids Research 35 (Web Server Issue): W310–3. doi:10.1093/nar/gkm218. PMC 1933236. PMID 17452349.
  171. A Avihoo, A Churkin and D Barash (2011). "RNAexinv: An extended inverse RNA folding from shape and physical attributes to sequences". BMC Bioinformatics 12 (319): 319. doi:10.1186/1471-2105-12-319. PMC 3176266. PMID 21813013.
  172. A. Levin, M. Lis, Y. Ponty, C. W. O’Donnell, S. Devadas, B. Berger, and J. Waldispühl (2012). "A global sampling approach to designing and reengineering RNA secondary structures". Nucleic Acids Research 40 (20): 10041–10052. doi:10.1093/nar/gks768. PMC 3488226. PMID 22941632.
  173. V Reinharz, Y. Ponty and Jérôme Waldispühl (2013). "A weighted sampling algorithm for the design of RNA sequences with targeted secondary structure and nucleotide distribution". Bioinformatics 29 (13): i308–i315. doi:10.1093/bioinformatics/btt217. PMC 3694657. PMID 23812999.
  174. M. C. Matthies, S. Bienert, and A. E. Torda (2012). "Dynamics in Sequence Space for RNA Secondary Structure Design". Journal of Chemical Theory and Computation 8 (10): 3663–3670. doi:10.1021/ct300276j.
  175. A. Taneda (2011). "MODENA: a multi-objective RNA inverse folding". Advances and Applications in Bioinformatics and Chemistry 4: 1–12. doi:10.2147/aabc.s14335. PMC 3169953. PMID 21918633.
  176. A. Taneda (2012). "Multi-Objective Genetic Algorithm for Pseudoknotted RNA Sequence Design". Frontiers in Genetics 3. doi:10.3389/fgene.2012.00036. PMC 3337422. PMID 22558001.
  177. A Esmaili-Taheri, M Ganjtabesh, M Mohammad-Noori (2014). "Evolutionary solution for the RNA design problem.". Bioinformatics 30 (9): 1250–1258. doi:10.1093/bioinformatics/btu001.
  178. R Kleinkauf, M Mann, R Backofen (2015). "antaRNA: ant colony-based RNA sequence design". Bioinformatics 31 (19): 3114–3121. doi:10.1093/bioinformatics/btv319.
  179. R Kleinkauf, T Houwaart, R Backofen, M Mann (2015). "antaRNA – Multi-objective inverse folding of pseudoknot RNA using ant-colony optimization". BMC Bioinformatics 16 (389). doi:10.1186/s12859-015-0815-6.
  180. C Flamm, I L Hofacker, S Maurer-Stroh, P F Stadler, M Zehl (2001). "Design of multistable RNA molecules.". RNA 7 (2): 254–265. doi:10.1017/s1355838201000863. PMC 1370083. PMID 11233982.
  181. G Rodrigo G and A Jaramillo (2014). "RiboMaker: computational design of conformation-based riboregulation.". Bioinformatics 30 (17): 2508–2510. doi:10.1093/bioinformatics/btu335. PMID 24833802.
  182. C Höner zu Siederdissen, S Hammer, I Abfalter, I L Hofacker, C Flamm, and P F Stadler (2013). "Computational Design of RNAs with Complex Energy Landscapes". Biopolymers 99 (12): 1124–1136. doi:10.1002/bip.22337. PMID 23818234.
  183. RB Lyngsø, J W J Anderson, E Sizikova, A Badugu, T Hyland, and Jotun Hein (2012). "Frnakenstein: multiple target inverse RNA folding". BMC Bioinformatics 13 (260): 260. doi:10.1186/1471-2105-13-260. PMC 3534541. PMID 23043260.
  184. W. Shu, M. Liu, H. Chen, X. Bo and S. Wang (2010). "ARDesigner: A web-based system for allosteric RNA design". Journal of Biotechnology 150 (4): 466–473. doi:10.1016/j.jbiotec.2010.10.067. PMID 20969900.
  185. Byun Y, Han K (2009). "PseudoViewer3: generating planar drawings of large-scale RNA structures with pseudoknots.". Bioinformatics 25 (11): 1435–7. doi:10.1093/bioinformatics/btp252. PMID 19369500.
  186. Byun Y, Han K (2006). "PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structures.". Nucleic Acids Res 34 (Web Server issue): W416–22. doi:10.1093/nar/gkl210. PMC 1538805. PMID 16845039.
  187. Han K, Byun Y (2003). "PSEUDOVIEWER2: Visualization of RNA pseudoknots of any type.". Nucleic Acids Res 31 (13): 3432–40. doi:10.1093/nar/gkg539. PMC 168946. PMID 12824341.
  188. Han K, Lee Y, Kim W (2002). "PseudoViewer: automatic visualization of RNA pseudoknots.". Bioinformatics. 18. Suppl 1 (Suppl 1): S321–8. doi:10.1093/bioinformatics/18.suppl_1.S321. PMID 12169562.
  189. Kaiser A, Krüger J, Evers DJ (2007). "RNA Movies 2: sequential animation of RNA secondary structures.". Nucleic Acids Res 35 (Web Server issue): W330–4. doi:10.1093/nar/gkm309. PMC 1933240. PMID 17567618.
  190. Evers D, Giegerich R (1999). "RNA movies: visualizing RNA secondary structure spaces.". Bioinformatics 15 (1): 32–7. doi:10.1093/bioinformatics/15.1.32. PMID 10068690.
  191. Tsang, Herbert H.; Dai, Denny C. (2012). "RNA-DV: an interactive tool for editing and visualizing RNA secondary structures". Proceeding BCB '12 Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine: 601–603. doi:10.1145/2382936.2383036.
  192. Martinez HM, Maizel JV, Shapiro BA (2008). "RNA2D3D: a program for generating, viewing, and comparing 3-dimensional models of RNA.". J Biomol Struct Dyn 25 (6): 669–83. doi:10.1080/07391102.2008.10531240. PMID 18399701.
  193. Reuter JS, Mathews DH (2010). "RNAstructure: software for RNA secondary structure prediction and analysis.". BMC Bioinformatics 11 (1): 129. doi:10.1186/1471-2105-11-129. PMC 2984261. PMID 20230624.
  194. Yang H, Jossinet F, Leontis N, Chen L, Westbrook J, Berman H, Westhof E (2003). "Tools for the automatic identification and classification of RNA base pairs.". Nucleic Acids Res 31 (13): 3450–60. doi:10.1093/nar/gkg529. PMC 168936. PMID 12824344.
  195. Menzel P, Seemann SE, Gorodkin J (2012). "RILogo: visualizing RNA-RNA interactions.". Bioinformatics 28 (19): 2523–6. doi:10.1093/bioinformatics/bts461. PMID 22826541.
  196. Darty K, Denise A, Ponty Y (2009). "VARNA: Interactive drawing and editing of the RNA secondary structure.". Bioinformatics 25 (15): 1974–5. doi:10.1093/bioinformatics/btp250. PMC 2712331. PMID 19398448.
This article is issued from Wikipedia - version of the Thursday, March 31, 2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.