Semiautomated improvement of RNA alignments
E. S. Andersen, A. Lind-Thomsen, B. Knudsen, S. E. Kristensen, J. H. Havgaard, E. Torarinsson, N. Larsen, C. Zwieb, P. Sestoft, J. Kjems and J. Gorodkin,
RNA 13:1850-1859, 2007.
NoFold is an approach for characterizing and clustering RNA secondary structures without computational folding or alignment. It works by mapping each RNA sequence of interest to a structural feature space, where each coordinate within the space corresponds to the probabilistic similarity of the sequence to an empirically defined structure model (e.g. Rfam family covariance models).
XRNA is a Java based suite of tools for the creation, annotation and display of RNA secondary structure diagrams.XRNA provides editing tools for easy modification of publication quality secondary diagrams that can be either drawn manually, or through automatic generation. Other features include grouping, numbering and structure annotation. XRNA secondary structures may be saved in a native format, or exported as postscript for printing and further manipulation in programs such as Adobe Illustrator.
Lorenz, Ronny and Bernhart, Stephan H. and Höner zu Siederdissen, Christian and Tafer, Hakim and Flamm, Christoph and Stadler, Peter F. and Hofacker, Ivo L. ViennaRNA Package 2.0
Algorithms for Molecular Biology, 6:1 26, 2011, doi:10.1186/1748-7188-6-26
ModeRNA is a program for comparative modeling of RNA 3D structures. It requires a pairwise sequence alignment and a structural template to generate a 3D structural model of the target RNA sequence via either a fully automated or script-based approaches. ModeRNA is capable of handling 115 different nucleotide modifications and bridging gaps using fragments derived from an extensive fragment library.
FRUUT computes an RNA structure alignment of two given RNA molecules. We generalize previous algorithms that either solved the problem in an asymmetric manner, or were restricted to the rooted and/or ordered cases. Focusing here on the most general unrooted unordered case, we show that our algorithm has an O(nTnS min(dT, dS)) time complexity, where nT and nS are the number of nodes and dT and dS are the maximum node degrees in the input trees T and S, respectively. This maintains (and slightly improves) the time complexity of previous, less general algorithms for the problem.