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

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BLAND

,Computational Prediction of RNA–RNA Interactions,s, namely the stability of the duplex between the two interacting RNAs and the internal structure of both mRNA and ncRNA. Thus, approaches can be distinguished into different major categories depending on how they consider inter- and intramolecular structure. The first class completely neglects the

overrule

SCFGs in RNA Secondary Structure Prediction : A Hands-on Approach,cussion to the use of grammars with additional information (such as evolutionary information) to improve the quality of predictions. Finally, we provide a brief survey of programs that use stochastic context-free grammars for RNA secondary structure prediction and modelling.

財(cái)政

Introduction to RNA Secondary Structure Comparison,quences (and of different length), we study variants of the tree edit model. We name some of the available tools and give pointers to the literature. We end with a short review on comparing structures with pseudo-knots as an unsolved problem and topic of active research.

遺忘

The Art of Editing RNA Structural Alignments,rations that go into constructing RNA structural alignments at the secondary and tertiary structure level; introduce software, databases, and algorithms that have proven useful in semiautomating the work process; and suggest future directions towards full automatization.

colony

Mirela Andronescu,Anne Condon,Douglas H. Turner,David H. Mathews

Mechanics

Stefan Washietl,Stephan H. Bernhart,Manolis Kellis

Fibrinogen

Kristian Rother,Magdalena Rother,Pawel Skiba,Janusz M. Bujnicki

財(cái)產(chǎn)

RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods

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