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Gathers an assortment of methods for RNA secondary structure analyses. ViennaRNA provides a unified interface to a set of command-line programs dealing with: (i) noncoding RNA detection, (ii) three different algorithms for structure prediction, (iii) RNA folding kinetics, (iv) sequence design considering RNA-RNA hybridizations, and (v) utilities that mainly assist in processing input- and output data and more.
RNAiFold / RNA Inverse Folding
A website that provides public access to the CPdesign and LNSdesign algorithms for solving the RNA inverse folding problem. RNAiFold 2.0 is a complete overhaul of RNAiFold 1.0, rewritten from the now defunct COMET language to C++. The new code properly extends the capabilities of its predecessor by providing a user-friendly pipeline to design synthetic constructs having the functionality of given Rfam families. In addition, the new software supports amino acid constraints, even for proteins translated in different reading frames from overlapping coding sequences; moreover, structure compatibility/incompatibility constraints have been expanded. With these features, RNAiFold 2.0 allows the user to design single RNA molecules as well as hybridization complexes of two RNA molecules.
A merge between RNAfbinv and incaRNAtion. incaRNAfbinv offers sequence design solutions that to the best of our knowledge are not available in neither the most recently published programs for RNA design, namely antaRNA and RNAiFold, nor any other such program that was devised since the seminal program called RNAinverse from the Vienna RNA package was put forth. It should be noted that incaRNAfbinv relies on other programs aside of RNAinverse that are available in the Vienna RNA package such as RNAfold that solves a direct problem at each iteration and RNAdistance. In addition to the design of synthetic regulatory sequences, it can be used as a pre-processing step for the detection of novel natural occurring RNAs. The web server is user-friendly and accessible to practitioners, both in terms of ease of use and simplification of the output. It serves experimental groups for improving their capability to perform RNA sequence design.
ERD / Evolutionary RNA Designer
Designs sequences that fold into a given target RNA secondary structure, i.e. whose minimum free energy (MFE) structure is the target structure. ERD is an evolutionary algorithm for RNA design problem which handles some sequence and energy constraints. In the sequence constraints, the user can restrict sequence positions to a fixed nucleotide or to a subset of nucleotides. As for the energy constraint, the user can specify an interval for the free energy ranges of the designed sequences. The designed RNA sequences in this method are more reliable and similar to the natural counterparts.
SynBioWave / Synthetic Biological software based on Google Wave
A Google Wave implementation for molecular biologists. SynBioWave aims to unite the stunning possibilities regarding a cooperative workflow of a web application with the comprehensive assortment of sequence tools a desktop application offers. The SynBioWave core consists of one robot, the SynBioWave robot and an associated gadget. Together, these programs generate a user interface, communicate with an internal database, and import or export annotated sequence formats.
RNA Designer
Takes as input a secondary structure description and outputs an RNA strand that is predicted to fold to that secondary structure. RNA Designer can be used to design RNA molecules with certain structural properties, as part of the development of molecules with novel functional properties, or more fundamentally in order to understand which secondary structure elements are critical to specific functions of cellular RNAs. RNA Designer uses a stochastic local search algorithm, which decomposes the input structure in a hierarchical fashion, finds strands that fold to the resulting substructures, and then attempts to combine the strands for substructures into a strand for the overall structure.
An interactive java application that performs RNA sequence design, constrained to yield a specific RNA shape and physical attributes. RNAexinv is an extended inverse RNA folding program with the rationale behind that the generated sequences should not only fold into a desired structure, but they should also exhibit favorable attributes such as thermodynamic stability and mutational robustness. RNAexinv considers not only the secondary structure in order to design sequences, but also the mutational robustness and the minimum free energy.
Provides a randomized search method that solves the RNA inverse folding problem. MCTS-RNA uses Monte Carlo tree search (MCTS). It can create a search tree where each node, any sequence space, corresponds to an assignment event. This tool provides an efficient way to search in the GC-content-specific sequence space. It can perform trial-and-error by setting up a search tree and allow backtracking when the current branch turns out to be non-promising according to the Upper Confidence Bound (UCB) score.
MODENA / Multi-Objective DEsign of Nucleic Acids
An RNA inverse folding program based on multi-objective genetic algorithm. MODENA explores the approximate set of weak Pareto optimal solutions in the objective function space of 2 objective functions, a structure stability score and structure similarity score. MODENA can simultaneously design multiple different RNA sequences at 1 run, whose lowest free energies range from a very stable value to a higher value near those of natural counterparts.
Provides a script collection for Benchmarks and Plots from the publication about the software RNAblueprint. RNAblueprint is like a library equipped with a flexible scripting interface where the user can easily implement its own optimization procedures and come up with new objective functions. RNAblueprint solves the problem of sampling RNA sequences compatible with multiple structural and sequence constraints in a well-defined way. In addition, this method can be easily integrated into existing tools.
Implements various estimators of mutual information. synRNASeqNet executes several estimator as Millow-Madow, Bayesian or the Chao-Shen. It offers wrappers to the k Nearest Neighbour (kNN) and kernel density estimators, and provides various index of performance evaluation such as precision, recall, False Positive Rate (FPR), F-Score, Receiver Operating Characteristic-Positive Rate (ROC-PR) Curves and so on. It provides a way of generating synthetic RNA-Seq Network with known dependence structure.
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