Dynalign: an algorithm for finding the secondary structure common to two RNA sequences.

By D. Mathews, Douglas H. Turner. Journal of Molecular Biology, 2002

417 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b0041d53e62792744fd12613e5fc06ab97197cca

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In Molecular Biology

Citations in the corpus

Inferring Noncoding RNA Families and Classes by Means of Genome-Scale Structure-Based Clustering (2007, background): “[26, 27] anddynalign [28] implement a more or less complete energy model for the RN A folding part.”
Knowledge-based machine learning methods for macromolecular 3D structure prediction (2016, background): “RNA tertiary structure prediction does not gain as much attention as secondary structure prediction (Akutsu, 2000; Alkan et al., 2006; Backofen et al., 2009; Bindewald and Shapiro, 2006; Eddy and Durbin, 1994; Ferretti and Sankoff, 1989; Gardner and Giegerich, 2004; Hamada et al., 2009; Havgaard et ”
ViennaRNA Package 2.0 (2011, methodology): “We refer to the well-established software tools FoldAlign [55], or DynAlign [56] for this task.”
RNAstructure: software for RNA secondary structure prediction and analysis (2010, methodology): “Alternatively, using two or more homologous sequences to determine a conserved structure can result in significantly more accurate structure prediction [23-27].”
A comprehensive comparison of comparative RNA structure prediction approaches (2004, methodology): “For data-sets consisting of short ( 200 bases) and diverse sequences Dynalign might do well or one might choose to use a mixture of RNAalifold or Pfold to fold similar clades and RNAforester or MARNA to align folded clades.”
A benchmark of multiple sequence alignment programs upon structural RNAs (2005, background): “Dynalign second edition [17,18] Simultaneously aligns and predicts the lowest free energy RNA secondary structure common to two sequences.”
RNAstructure: web servers for RNA secondary structure prediction and analysis (2013, background): “Dynalign (17,21,32) Calculate the lowest free energy secondary structures common to two unaligned sequences.”
Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction (2004, methodology): “Both mfold and RNAstructure was run with MAX = 750 P = 20 W = 0 and efn2 rearrangement as recommended by [7].”
32 High-resolution cryo-electron microscopy structure of the Trypanosoma brucei ribosome (2013, methodology): “Multilign uses Dynalign (Mathews & Turner, 2002), which folds and aligns two sequences simultaneously without requiring any sequence identity; its structure prediction quality will therefore not be affected by input sequence diversity.”
CMfinder - a covariance model based RNA motif finding algorithm (2006, methodology): “The complexity of this algorithm is approximately quadratic in the length of the candidates, thus far more efficient than the Sankoff-style algorithms (Sankoff, 1985; Gorodkin et al., 1997; Mathews & Turner, 2002).”
PicXAA-R: Efficient structural alignment of multiple RNA sequences using a greedy approach (2011, methodology): “Hence, several studies have proposed various approximations to the Sankoff algorithm [5-19].”
Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework (2008, methodology): “As representatives of the exiting methods, we selected the five latest methods, Murlet [10], MXSCARNA [14], RNA Sampler [11], LaRA [9] and MASTR [13], which reportedly outperformed the other methods, including FoldalignM [8], RNAcast [3], Dynalign [2] and Stemloc [4], consistently.”
LocARNA-P: accurate boundary prediction and improved detection of structural RNAs. (2012, methodology): “…similarities and to derive consensus structure patterns for structural RNAs with low sequence identity (Sankoff 1985; Gorodkin et al. 1997; Mathews and Turner 2002; Ho¨chsmann et al. 2003; Hofacker and Stadler 2004; Havgaard et al. 2005; Siebert and Backofen 2005; Will et al. 2007; Bradley…”