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.

Single sequence tertiary structure prediction

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.

Intermolecular interactions: RNA-RNA

Many ncRNAs function by binding to other RNAs. For example, miRNAs regulate protein coding gene expression by binding to 3' UTRs, small nucleolar RNAs guide post-transcriptional modifications by binding to rRNA, U4 spliceosomal RNA and U6 spliceosomal RNA bind to each other forming part of the spliceosome and many small bacterial RNAs regulate gene expression by antisense interactions E.g. GcvB, OxyS and RyhB.
NameDescriptionIntra-molecular structureComparativeLinkReferences
RNApredatorRNApredator uses a dynamic programming approach to compute RNA-RNA interaction sites.
GUUGleA utility for fast determination of RNA-RNA matches with perfect hybridization via A-U, C-G, and G-U base pairing.
IntaRNAEfficient target prediction incorporating the accessibility of target sites.
CopraRNATool for sRNA target prediction. It computes whole genome predictions by mix of distinct whole genome IntaRNA predictions.
MINTAutomatic tool to analyze three-dimensional structures of RNA and DNA molecules, their full-atom molecular dynamics trajectories or other conformation sets. For each RNA or DNA conformation MINT determines the hydrogen bonding network resolving the base pairing patterns, identifies secondary structure motifs and pseudoknots. Also estimates the energy of stacking and phosphate anion-base interactions.
NUPACKComputes 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.
OligoWalk/RNAstructurePredicts bimolecular secondary structures with and without intramolecular structure. Also predicts the hybridization affinity of a short nucleic acid to an RNA target.
piRNACalculates 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.
RNAripalignCalculates 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.
RactIPFast and accurate prediction of RNA-RNA interaction using integer programming.
RNAaliduplexBased on RNAduplex with bonuses for covarying sites
RNAcofoldWorks much like RNAfold, but allows specifying two RNA sequences which are then allowed to form a dimer structure.
RNAduplexComputes optimal and suboptimal secondary structures for hybridization. The calculation is simplified by allowing only inter-molecular base pairs.
RNAhybridTool to find the minimum free energy hybridisation of a long and a short RNA.,
RNAupCalculates the thermodynamics of RNA-RNA interactions. RNA-RNA binding is decomposed into two stages. First the probability that a sequence interval remains unpaired is computed. Then the binding energy given that the binding site is unpaired is calculated as the optimum over all possible types of bindings.

Intermolecular interactions: MicroRNA:any RNA

The below table includes interactions that are not limited to UTRs.
NameDescriptionCross-speciesIntra-molecular structureComparativeLinkReferences
comTARA a web tool for the prediction of miRNA targets that is mainly based on the conservation of the potential regulation in plant species.
RNA22The first link 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 first finds putative microRNA binding sites in the sequence of interest, then identifies the targeted microRNA. Both tools are provided by the at .
RNAhybridTool to find the minimum free energy hybridisation of a long and a short RNA.,
miRBookingSimulates 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.,

Intermolecular interactions: MicroRNA:UTR

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,, or
NameDescriptionCross-speciesIntra-molecular structureComparativeLinkReferences
CupidMethod for simultaneous prediction of miRNA-target interactions and their mediated competing endogenous RNA 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.
Diana-microTVersion 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.
MicroTarAn animal miRNA target prediction tool based on miRNA-target complementarity and thermodynamic data.
miTargetmicroRNA target gene prediction using a support vector machine.
miRrorBased 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
PicTarCombinatorial microRNA target predictions.
PITAIncorporates the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition., ,
RNA22The first link 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 first finds putative microRNA binding sites in the sequence of interest, then identifies the targeted microRNA. Both tools are provided by the at .
RNAhybridTool to find the minimum free energy hybridisation of a long and a short RNA.,
SylamerMethod 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.
TAREFTARget REFiner 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.
p-TAREFplant TARget REFiner 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 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.
TargetScanPredicts 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.,

ncRNA gene prediction software

Family specific gene prediction software

RNA homology search software

Benchmarks

Alignment viewers, editors

Inverse folding, RNA design

;Notes:

Secondary structure viewers, editors