By Rick Russell (auth.), Rick Russell (eds.)
This quantity, written through specialists within the box, discusses the present knowing of the biophysical rules that govern RNA folding, with featured RNAs together with the ribosomal RNAs, viral RNAs, and self-splicing introns. as well as the elemental beneficial properties of RNA folding, the crucial experimental and computational techniques within the box are awarded with an emphasis on their person strengths and obstacles, and the way they are often mixed to be extra strong than any approach by myself; those methods contain NMR, unmarried molecule fluorescence, site-directed spin labeling, constitution mapping, comparative series research, graph thought, course-grained 3D modeling, and extra. This quantity could be of curiosity to expert researchers and complicated scholars getting into the sector of RNA folding.
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Extra info for Biophysics of RNA Folding
2004). , topological descriptors) of RNA motifs (Kim et al. 2004; Gevertz et al. 2005). Laplacian eigenvalues (Fera et al. 2004; Gan et al. 2004; Kim et al. 2004) or graph diameters (Gevertz et al. 2005) are examples of topological descriptors. 3 Graph Applications to RNA 33 Fig. 4 Existing RNAs shown as tree and dual graphs. The Simian Retrovirus Type-1 (SRV-1) containing an H-type pseudoknot can only be represented by a dual graph. The topology ID and the second eigenvalue are labeled below each graph The Laplacian is a matrix that describes graph connectivity [see Figs.
Univie. 1 Available computational software to predict RNA secondary structures (Mfold, Vienna RNAFold), predict the 3D folding of RNA (MC-Sym, FARNA), coarse grain RNAs (NAST, iFoldRNA), detect secondary and tertiary motifs (FR3D, RNAMotif, RMDetect), construct 3D models of RNA structures (Assemble, RNA2D3D, RNABuilder), search for folded sequences on a certain structure (RNAInverse, NUPACK, EteRNA), as well as investigate motifs such as various loops and pseudoknots (Rloom, PKNOTS) Area Programs Methods Laboratory (reference, URL) 28 N.
The graph merge method, which was developed to predict larger RNA topologies by the Knisley group, has similar prediction levels compared to our clustering approaches for tree graphs with 7 and 8 vertices (Koessler et al. 2010). Modular design approaches by build-up as used for proteins have been used to identify possible sequences that may fold into some candidate topologies (Kim et al. 2004; Izzo et al. 2011). In addition, graph representations have been applied in the design of synthetic RNAs by providing target topologies for designing and screening pools used in in vitro selection (Gevertz et al.
Biophysics of RNA Folding by Rick Russell (auth.), Rick Russell (eds.)