Method | Description | Size limit | Reference |
Afold | Evaluates internal loops of RNA secondary structure with optimized nearest-neighbor model energy functions (version 11.01.2006). | --- |
Ogurtsov et al. 2006 |
Carnac | Combines three features: energy minimization, phylogenetic comparison and sequence conservation in order to predict an RNA secondary structure (version 2008, pre 0.34). | --- |
Touzet and Perriquet, 2004 |
CentroidAlifold | An extension of the CentroidFold program which takes as an input multiple sequences (version 0.0.9). | --- |
Hamada et al 2011 |
CentroidFold | Uses generalized centroid estimators which maximize the expected weighted true predictions of base pairs in the predicted structure (version 0.0.9). | --- |
Sato et al 2009 |
ContextFold | Uses rich parameterized machine learning models (over 70,000 free parameters - version 1.0). | --- |
Zakov and Ziv-Ukelson, 2011 |
Contrafold | Uses conditional log-linear models (CLLMs), a flexible class of probabilistic models which generalize upon stochastic context-free grammars (SCFGs) by using discriminative training and feature-rich scoring (version 2.02). | --- |
Do et al. 2006 |
DAFS | Simultaneous aligning and folding of RNA sequences by dual decomposition (version 0.0.2, Sep 15, 2012 + Vienna 1.8.5 + GLPK 4.45). | --- |
Sato et al., 2012 |
DotKnot | DotKnot is a heuristic method for pseudoknot prediction in a given RNA sequence. DotKnot extracts stem regions from the secondary structure probability dot plot calculated by RNAfold. Recursive H-type pseudoknots and intramolecular kissing hairpins are constructed and their presence in the sequence is verified. The detected pseudoknots can then be further analysed using bioinformatics or laboratory technique (ver 1.3.1). | --- |
Sperschneider and Datta, 2010 |
Fold | A program from the RNAstructure package for single sequence secondary structure prediction by free energy minimization (RNAstructure ver 5.3). | --- |
Reuter & Mathews, 2010 |
HotKnots | A heuristic algorithm which iteratively forms stable stems using a free energy minimization criterion to identify promising candidate stems (version 2.0). | 500 nt |
Renet al. 2005 |
IPknot | Predicts the maximum expected accuracy (MEA) structure using integer programming with a threshold cut (version 0.0.2). | --- |
Sato et al, 2011 |
MCFold | MC-Fold uses a Nucleotide Cyclic Motif (NCM) fusion process to generate a pool of secondary structures, from which the final prediction is selected (version Mar 17 2008 17:48:11). | --- |
Parisien & Major, 2008 |
MXScarna | Performs fast structural multiple alignment of RNA sequences using a progressive alignment based on the pairwise structural alignment algorithm of SCARNA (ver. 2.1). | --- |
Tabei and Asai, 2009 |
Mastr | Uses a MCMC sampling approach 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 base pair probabilities (ver. 1.0). | --- |
Lindgreen et al. 2007 |
MaxExpect | A program from the RNAstructure package for secondary structure prediction by maximizing expected accuracy (RNAstructure ver 5.3). | --- |
Gloor & Matthews, 2009 |
McQFold | Markov Chain Monte Carlo (MCMC) sampling of secondary structures with pseudoknots (version 30.05.2006). | --- |
Metzler & Nebel 2008 |
Multilign | Finds the lowest free energy secondary structure common to more than two homologous sequences. Uses multiple iterations of Dynalign to predict the conserved structure (RNAstructure ver 5.3). | --- |
Xu and Matthews, 2010 |
Murlet | A variant of the Sankoff algorithm, which uses an efficient scoring system that reduces the time and space requirements (version 0.0.1). | --- |
Kiryu et al. 2007 |
PETfold_ver_20 | Predicts the consensus RNA secondary structure from an RNA alignment (release from May 20, 2013, last modified at May 20, 2013). Uses Vienna 1.8.5. | --- |
Seemann et al, 2008 |
PETfold_ver_pre_20 | Predicts the consensus RNA secondary structure from an RNA alignment (version 2.0pre - pre-release from Nov 3, 2011, last modified at Nov 3, 2011). Uses Vienna 1.8.5. | --- |
Seemann et al, 2008 |
PPfold | A new version of Pfold that can predict the consensus secondary structure of RNA alignments through a stochastic context-free grammar coupled to an evolutionary model (version 2.0). | --- |
Sükösd et al, 2011 |
Pknots | A dynamic programming algorithm for "optimal" RNA pseudoknot prediction (version 1.05). Uses the Turnes rules and finds the minimum free energy structure. | --- |
Rivas & Eddy, 1999 |
PknotsRG | PKnotsRG uses the same model that PKNOTS but instead of finding the optimal minimum free energy, it applies heuristic approach. It does not guarantee to find the mininum free energy structure. PknotsRG is dedicated to pseudoknot prediction (version 1.03). | --- |
Reeder et al. 2007 |
ProbKnot | A program from the RNAstructure package for fast prediction of RNA secondary structure including pseudoknots. Assembles maximum expected accuracy structures from computed base-pairing probabilities (RNAstructure ver 5.3). | --- |
Bellaousov & Matthews, 2010 |
RNASLOpt | Predicts stable, locally optimal secondary structures represented by stack configurations (version 2011-11-01). | --- |
Li and Zhang, 2011 |
RNASampler | A sampling-based program that predicts common RNA secondary structure motifs in a group of related sequences (ver. 1.3). | --- |
Xu and Stormo, 2007 |
RNAalifold | Computes the minimum free energy structure that is simultaneously formed by a set of aligned sequences. Additionally, uses sophisticated handling of alignment gaps, and RIBOSUM-like scoring matrices (Vienna Package ver. 1.8.3). | --- |
Bernhart et al. 2008 |
RNAfold | RNA structure prediction program that comes with the Vienna package. Predicts MFE structures and base pair probabilities based on the dynamic programming algorithm originally developed by M. Zuker and P. Stiegler. The partition function algorithm is based on work by McCaskill (Vienna Package ver. 1.8.3). | --- |
Hofacker 2004 |
RNAshapes | Unique suboptimal structures (shapes) are selected based on an abstract representation of RNA secondary structure which is inspired by the dot bracket representation known from the Vienna RNA package. The user can choose from five different types of shape resolution corresponding to different abstraction levels (version 2.1.5). | 500 nt |
Steffen et al. 2006 |
RNAsubopt | Calculates all suboptimal secondary structures within a user defined energy range above the MFE (Vienna Package ver. 1.8.3). | 500 nt |
Hofacker 2004 |
RNAwolf | Predicts an extended structure (including non-canonical base-pairs and structures composed of 2-diagrams). The allowed base-pairs can contain all 4x4 nucleotides and the nucleotide bonds are explicitly annotated with the paired edges and isostericity information (version 0.3.2.0). | 2000 nt |
Höner zu Siederdissen et al, 2011 |
RSpredict | Takes into account sequence covariation and employs effective heuristics for improving accuracy (ver. 26.05.2009). | --- |
Spirollari et al. 2009 |
Sfold | Statistical sampling of all possible structures. The sampling is weighted by partition function probabilities. The ensemble centroid (EC) structure is used as a final prediction (ver. 2.0-20080807). | --- |
Ding et al. 2004 |
TurboFold | The base pairing probabilities for a sequence are estimated by combining intrinsic information, derived from the sequence itself via the nearest neighbor thermodynamic model, with extrinsic information, derived from the other sequences in the input set. For a given sequence, the extrinsic information is computed by using pairwise-sequence-alignment-based probabilities for co-incidence with each of the other sequences, along with estimated base pairing probabilities, from the previous iteration, for the other sequences (RNAstructure ver 5.3). | --- |
Harmanci et al, 2011 |
UNAFold | An integrated collection of programs that simulate folding, hybridization, and melting pathways for one or two single-stranded nucleic acid sequences. Folding (secondary structure) prediction for single-stranded RNA or DNA combines free energy minimization, partition function calculations and stochastic sampling (version 3.8). | 8000 nt |
Markham and Zuker, 2008 |