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A service allowing the online computation of 3D structure based multiple RNA sequence alignments. The server makes it possible to combine sequences with and without known 3D structures. Given a set of sequences SARA-Coffee outputs a multiple sequence alignment along with a reliability index for every sequence, column and aligned residue. SARA-Coffee combines SARA, a pairwise structural RNA aligner with the R-Coffee multiple RNA aligner in a way that has been shown to improve alignment accuracy over most sequence aligners when enough structural data is available.
A user-friendly online interface for the alignment of RNA 3D structures. WebSTAR3D globally aligns RNA structures with a two-step strategy: first, it finds the consensus of stacks between the structures using 2D topology and 3D geometry; then, it uses this information to guide the alignment of loop regions. The stack and loop alignments are then combined into the final result. This powerful approach avoids complex and expensive secondary structure comparison and base matching, making the running time feasible for the comparison of large RNAs. Yet, it matches the prediction accuracy of state-of-the-art tools.
DIAL / DIhedral ALignment Server
Provides public access to a dynamic programming algorithm for pairwise 3D structural alignment of RNA. DIAL achieves quadratic time by performing an alignment that accounts for (i) pseudo-dihedral and/or dihedral angle similarity, (ii) nucleotide sequence similarity and (iii) nucleotide base-pairing similarity. DIAL provides access to three alignment algorithms: global (Needleman-Wunsch), local (Smith-Waterman) and semiglobal (modified to yield motif search).
ARTS / Alignment of RNA Tertiary Structures
A web server built around ARTS, a method for aligning tertiary structures of nucleic acids (both RNA and DNA). ARTS receives a pair of 3D nucleic acid structures and searches for a priori unknown common substructures. The search is truly 3D and irrespective of the order of the nucleotides on the chain. The identified common substructures can be large global folds with hundreds and even thousands of nucleotides as well as small local motifs with at least two successive base pairs.
RMfam / RNA Motif Families
A database of annotated multiple sequence alignments and probabilistic models for a number of RNA motifs. RMfam presents 34 alignments, consensus structures and corresponding probabilistic models of published RNA motifs. For the purposes of this work an RNA motif is a recurring RNA sequence and/or secondary structure found within larger structures that can be modelled by either a covariance model or a profile HMM. RMfam is modelled loosely on the Rfam and Pfam databases and draws a lot of ideas from these resources. We have proven the accuracy using benchmarks, and the utility of this resource for alignment curation, evolutionary analyses and shown that it has some promise for the prediction of RNA function.
R3D Align
Decomposes 3D structure into sets of local nucleotide neighbourhoods, which typically overlap in the sense that each nucleotide is included in more than one set. R3D Align is a web server that for locally optimized, nucleotide to nucleotide pairwise alignments of RNA 3D structures. It also provides additional features: all RNA chains present in the protein data bank (PDB) file are dynamically loaded into the input page to allow the user to specify chains and nucleotide ranges to align.
Allows multiple alignment of RNA molecules. CARNA does not pick the most likely consensus structure, but computes the alignment that fits best to all likely structures simultaneously. Hence, CARNA is particularly useful when aligning RNAs like riboswitches, which have more than one stable structure. Also, CARNA is not limited to nested structures, but is able to align arbitrary pseudoknots. CARNA requires only the RNA sequences as input and will compute base pair probability matrices and align the sequences based on their full ensembles of structures. Alternatively, users can also provide base pair probability matrices (dot plots in .ps format) or fixed structures (as annotation in the FASTA alignment) for the input sequences.
RASS / RNA alignment in the joint Sequence-Structure space
Provides a tool for users to compare and align two RNA molecules in the joint sequence-structure space. The user will provide two RNA molecules as input where one may be a RNA molecule with known function and the other is a RNA molecule the user may want to know more about. After alignment of the two molecules, the user can look at the structure alignment using Jmol to identify the structural similar regions and dissimilar regions to infer how the two molecules may share similar function while differ in some substrate specificities. From the sequence alignment, the user can identify conserved nucleotides. Here, those nucleotides that align well in sequence space are also spatially close on structure space since RASS aligns both sequence and structure simultaneously. From the aligned nucleotides, the user can gain more insight on the functional and/or evolutionary relationship of the two molecules.
Web-Beagle / Web-BEar Alignment Globla and Local
A web server for the pairwise global or local alignment of RNA secondary structures. The server exploits a new encoding for RNA secondary structure and a substitution matrix of RNA structural elements to perform RNA structural alignments. The web server allows the user to compute up to 10 000 alignments in a single run, taking as input sets of RNA sequences and structures or primary sequences alone. In the latter case, the server computes the secondary structure prediction for the RNAs on-the-fly using RNAfold (free energy minimization). The user can also compare a set of input RNAs to one of five pre-compiled RNA datasets including lncRNAs and 3′ UTRs. All types of comparison produce in output the pairwise alignments along with structural similarity and statistical significance measures for each resulting alignment. A graphical color-coded representation of the alignments allows the user to easily identify structural similarities between RNAs. Web-Beagle can be used for finding structurally related regions in two or more RNAs, for the identification of homologous regions or for functional annotation.
An RNA 3D structural alignment tool to take into full account the 2D relations between stacks without the complicated comparison of secondary structures. First, the 3D conserved stacks in the inputs are identified and then combined into a tree-like consensus. Afterward, the loop regions are compared one-to-one in accordance with their relative positions in the consensus tree. The experimental results show that the prediction of STAR3D is more accurate for both non-homologous and homologous RNAs than other state-of-the-art tools with shorter running time.
Simultaneously aligns and folds RNA sequences based on maximizing expected accuracy of a predicted common secondary structure and its alignment. DAFS decomposes the pairwise structural alignment problem into two independent secondary structure prediction problems and one pairwise (non-structural) alignment problem by the dual decomposition technique, and maintains the consistency of a pairwise structural alignment by imposing penalties on inconsistent base pairs and alignment columns that are iteratively updated. Furthermore, we extend DAFS to consider pseudoknots in RNA structural alignments by integrating IPknot for predicting a pseudoknotted structure.
A structural RNA sequence alignment program on the basis of MOGA. Cofolga2mo is designed for global pairwise sequence alignment. By performing a BRAliBase 2.1 benchmark test, we found that the approximate set for RNA sequence alignments contain high-quality alignments comparable to the alignments obtained by the other recent mono-objective structural RNA alignment programs. Moreover, we found that Cofolga2mo can give accurate tRNA and 5S rRNA alignments comparable to the suboptimal alignments by Dynalign with much smaller computational resources.
BoulderALE / Boulder Alignment Editor
Allows for the annotation of Watson-Crick and non-Watson-Crick basepairs, annotation of features (i.e. stems, loops, etc.), collapsing of features (horizontal) and sequences (vertical), along with 2D display of sequences (using VARNA) and base composition given a secondary structure (using KiNG). BoulderALE is a lightweight editor for editing and assessing the quality of small RNA alignments (less than ~1000 nts and ~1000 sequences). BoulderALE was developed to evaluate structure backed RNA alignments, along with the ability to collapse the alignment horizontally, to hide gapped regions of the alignment.
A method for aligning two RNA secondary (2D) structures that possess coaxial helical stacking (CHS) motifs within the junctions of the two RNA structures. CHSalign is intended to be an efficient alignment tool for RNAs containing similar junctions. Experimental results based on thousands of alignments demonstrate that CHSalign can align two RNA secondary structures containing CHS motifs more accurately than other RNA secondary structure alignment tools. CHSalign yields a high score when aligning two RNA secondary structures with similar CHS motifs or helical arrangement patterns, and a low score otherwise.
An implementation of a pairwise stochastic context-free grammar for RNA structural alignment. We use probabilistic models (pair stochastic context-free grammars, pairSCFGs) as a unifying framework for scoring pairwise alignment and folding. A constrained version of the pairSCFG structural alignment algorithm was developed which assumes knowledge of a few confidently aligned positions (pins). These pins are selected based on the posterior probabilities of a probabilistic pairwise sequence alignment. The proposed grammar is both structurally unambiguous and alignment unambiguous.
Simulates multiple alignments of a given average dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Currently this software implements a mono and dinucleotide model which should be sufficient for many applications.
A tool for superposition of multiple RNA structures. It is based on a pairwise RNA superposition algorithm called SETTER. The main idea of MultiSETTER is to build an average structure and to superpose all the input structure onto this average structure. For building the average structure we implemented a modified version of Clustal algorithm known from the sequence domain. The modification consists in replacing the sequence specific parts with their structure analogs. Thus, instead of adding sequences one by one into a resulting multiple sequence alignment as Clustal does, MultiSETTER iteratively merges RNA structures to form a resulting average structure.
Implements an algorithm which iteratively uses a sequence-structure alignment procedure to build a multiple RNA structure alignment. PMFastR has low memory consumption allowing for the alignment of large sequences such as 16S and 23S rRNA. The algorithm also provides a method to utilize a multi-core environment. Finally, results on benchmark data sets from BRAliBase shows that PMFastR outperforms other state-of-the-art programs. Furthermore, PMFastR regenerates 607 Rfam seed alignments and shows that its automated process creates similar multiple alignments to the manually-curated Rfam seed alignments.
Delivers a suite of RNA analysis functions for inferring RNAs’ relationship based on comparing their secondary-structures. Functions include i) visualization of numerical representation of RNA secondary structure; ii) detection of single-point mutation based on secondary structure; and iii) comparison of pairwise and multiple RNA secondary structures. RNA-TVcurve is very useful for making deleterious mutation prediction, RNA structural feature extraction and multiple RNA structural comparison.
A web server for aligning multiple RNA sequences by extending CentroidAlign, which is a fast and accurate multiple aligner for RNA sequences that considers secondary structures. We showed that CentroidAlign-Web is capable of dealing with long RNA sequences, such as rRNAs, and that information about secondary structures can be used to improve the accuracy of multiple alignments. It has an interface in which users can specify a region of the human genome (hg18) from which to extract a multiple alignment, and re-align that region using CentroidAlign.
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