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

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書目名稱RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods
編輯Jan Gorodkin,Walter L. Ruzzo
視頻videohttp://file.papertrans.cn/821/820192/820192.mp4
概述Presents current up-to-date methodologies.Features tips on trouble shooting and avoiding known pitfalls.Contains key notes and implementation advice from the experts.Includes supplementary material:
叢書名稱Methods in Molecular Biology
圖書封面Titlebook: RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods;  Jan Gorodkin,Walter L. Ruzzo Book 2014 Springer Science+Bu
描述.The existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950‘s, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes.? However, a long series of striking discoveries, from RNA‘s ability to carry out catalytic function, to discovery of riboswitches, microRNAs and other ribo-regulators performing critical tasks in essentially all living organisms, has created a burgeoning interest in this primordial component of the biosphere.? However, the structural characteristics and evolutionary constraints on RNA molecules are very different from those of proteins, necessitating development of a completely new suite of informatic tools to address these challenges. In .RNA Sequence, .Structure, Function: Computational and Bioinformatic Methods., expert researchers in the field describe a substantial and relevant fraction of these methodologies from both practical and computational/algorithmic perspectives. Focusing on both of these directions addresses both the biologist interested in knowing more about RNA bioinformatics as well as the bioinformaticist interested in
出版日期Book 2014
關(guān)鍵詞De novo search for structured RNAs; Homology search; RNA 3D Structure; RNA 3D modeling; RNA Bioinformati
版次1
doihttps://doi.org/10.1007/978-1-62703-709-9
isbn_softcover978-1-4939-6165-8
isbn_ebook978-1-62703-709-9Series ISSN 1064-3745 Series E-ISSN 1940-6029
issn_series 1064-3745
copyrightSpringer Science+Business Media New York 2014
The information of publication is updating

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Energy-Based RNA Consensus Secondary Structure Prediction in Multiple Sequence Alignments,gorithms. Here we describe the theory and applications of the RNAalifold algorithm. Consensus secondary structure prediction not only leads to significantly more accurate structure models, but it also allows to study structural conservation of functional RNAs.
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, Discovery of Structured ncRNA Motifs in Genomic Sequences,ch based on the CMfinder program as a case study. Applications to genomic screens for novel . structured ncRNAs, including structured RNA elements in untranslated portions of protein-coding genes, are presented.
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Energy-Directed RNA Structure Prediction, in thermodynamic equilibrium. However, especially for long RNAs, this need not be the case. In the last section we therefore discuss approaches for predicting RNA folding kinetics and co-transcriptional folding.
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Automated Modeling of RNA 3D Structure,he ParAlign and Infernal programs on RNA family data from Rfam. We also briefly summarize template-free methods for RNA 3D structure prediction. Typically, RNA structures generated by automated modeling methods require local or global optimization. Thus, we also discuss methods that can be used for local or global refinement of RNA structures.
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Concepts and Introduction to RNA Bioinformatics,ods for interactions between RNA and proteins..Here, we introduce the basic concepts of predicting RNA secondary structure relevant to the further analyses of RNA sequences. We also provide pointers to methods addressing various aspects of RNA bioinformatics and computational RNA biology.
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Annotating Functional RNAs in Genomes Using Infernal,he Rfam database are used to identify RNAs in the genome of the archaeon ., uncovering some additional RNAs not present in the genome’s initial annotation. Analysis of the results and comparison with family-specific methods demonstrate some important strengths and weaknesses of this general approach.
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