Titlebook: RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods; Jan Gorodkin,Walter L. Ruzzo Book 2014 Springer Science+Bu

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SCFGs in RNA Secondary Structure Prediction : A Hands-on Approach,in RNA secondary structure prediction. In this chapter, we discuss the basic SCFG algorithms (CYK and inside–outside algorithms) in an application-centered manner and use the pfold grammar as a case study to show how the algorithms can be adapted to a grammar in a nonstandard form. We extend our dis

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Annotating Functional RNAs in Genomes Using Infernal,e not routinely annotated in published genomes. Several programs have been developed for identifying RNAs, including specific tools tailored to a particular RNA family as well as more general ones designed to work for any family. Many of these tools utilize covariance models (CMs), statistical model

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Class-Specific Prediction of ncRNAs, sequence motifs and/or common secondary structure features. The detection of new members of RNA classes, as well as the comprehensive annotation of genomes with members of RNA classes is a challenging task that goes beyond simple homology search. Computational methods addressing this problem typica

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Abstract Shape Analysis of RNA,shapes classify competing secondary structures into classes that are defined by their arrangement of helices. It allows us to compute, in addition to the structure of minimal free energy, a set of structures that represents relevant and interesting structural alternatives. Furthermore, it allows to

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Introduction to RNA Secondary Structure Comparison,ucture representations and discuss their suitability for structure comparison. Then, we take a look at the more commonly used methods, restricting ourselves to structures without pseudo-knots. For comparing structures of the same sequence, we study base pair distances. For structures of different se

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RNA Structural Alignments, Part I: Sankoff-Based Approaches for Structural Alignments,for structural alignment is based on the principles proposed by Sankoff more than 25 years ago. The Sankoff algorithm simultaneously folds and aligns two or more sequences. The advantage of this algorithm over those that separate the folding and alignment steps is that it makes better predictions. T

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RNA Structural Alignments, Part II: Non-Sankoff Approaches for Structural Alignments,ry structure and the score of the alignment, is too high for long sequences (.(..) time for two sequences of length .). In this chapter, we introduce the methods that predict the structures and the alignment separately to avoid the heavy computations in Sankoff algorithm. In those methods, neither o

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, Discovery of Structured ncRNA Motifs in Genomic Sequences,ogy. This chapter outlines the challenges presented by this problem, together with some approaches towards solving them, with an emphasis on an approach based on the CMfinder program as a case study. Applications to genomic screens for novel . structured ncRNAs, including structured RNA elements in

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