Calculating nucleic acid secondary structure

Current Opinion in Structural Biology

Volumn 10, Issue 3, 2000, Pages 303-310

  Zuker, Michael ^a  

^a WASHINGTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

RNA;

ALGORITHM; COMPUTER ANALYSIS; DATA BASE; PHYLOGENY; PRIORITY JOURNAL; REVIEW; RNA SEQUENCE; RNA STRUCTURE;

EID: 0034070995     PISSN: 0959440X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-440X(00)00088-9     Document Type: Review

References (121)

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110. Zuker M., Jacobson A.B. Using reliability information to annotate RNA secondary structures. RNA. 4:1998;669-679. If users won't look at dot plot or other abstract measures of well definedness, then computed foldings can be annotated with this information. Colors are used to annotate bases or base pairs. The range of colors is red→orange→yellow→green→cyan→blue→violet→blac k; indicating best to worst defined. The software can handle any measure of well definedness.
111. Evers D., Giegerich R. RNA Movies: visualizing RNA secondary structure spaces. Bioinformatics. 15:1999;32-37. 'RNA Movies' is a dream come true, but it should not be taken too literally. The foldings are given, but transitions between foldings, especially minimum energy foldings for elongating chains, are automatically modeled and displayed in motion picture form. The user can watch the folding add one base pair at a time or switch dramatically from one conformation to a totally new one.
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119. Lowe T.M., Eddy S.R. A computational screen for methylation guide snoRNAs in yeast. Science. 283:1999;1168-1171. This is a beautiful combination of computational and laboratory work. An algorithm found guide RNAs for almost all ribosomal methylation sites in yeast. These were then verified in the laboratory by a combination of knockout experiments.
120. Erdmann V.A., Szymanski M., Hochberg A., de Groot N., Barciszewski J. Collection of mRNA-like non-coding RNAs. Nucleic Acids Res. 27:1999;192-195. This little-known database has accumulated a number of biological curiosities. These genes are transcribed, spliced and polyadenylated, and yet they do not code for proteins. They act as RNAs.
121. Ding Y., Lawrence C.E. A Bayesian statistical algorithm for RNA secondary structure prediction. Comput Chem. 23:1999;387-400. The authors generalize the RNA folding model to allow the energy parameters to be random variables. A partition function is computed for this expanded model. A statistically valid sample of suboptimal foldings is generated by performing random tracebacks using the conditional probabilities generated during the computation of the partition function. This method is still in its infancy, but it has potential to solve problems that have been considered intractable to the present.