Titlebook: RNA Bioinformatics; Ernesto Picardi Book 2021Latest edition Springer Science+Business Media, LLC, part of Springer Nature 2021 Computation

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书目名称RNA Bioinformatics影响因子(影响力)




书目名称RNA Bioinformatics影响因子(影响力)学科排名




书目名称RNA Bioinformatics网络公开度




书目名称RNA Bioinformatics网络公开度学科排名




书目名称RNA Bioinformatics被引频次




书目名称RNA Bioinformatics被引频次学科排名




书目名称RNA Bioinformatics年度引用




书目名称RNA Bioinformatics年度引用学科排名




书目名称RNA Bioinformatics读者反馈




书目名称RNA Bioinformatics读者反馈学科排名

inferno

CRAMP

Computational Analysis of circRNA Expression Data,ally reproducible analysis of circRNA expression starting for a public RNA-Seq experiment. The main steps of circRNA prediction, annotation, classification, sequence reconstruction, quantification, and differential expression are illustrated.

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制定

Advanced Design of Structural RNAs Using RNARedPrint,erties. This chapter describes how to use the software . for the de novo rational design of RNA sequences adopting one or several desired secondary structures. Depending on the application, these structures could represent alternate configurations or kinetic pathways. The software makes such design

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Modeling and Predicting RNA Three-Dimensional Structures,cs-based approaches and molecular dynamics simulations are not tractable on large molecules with all-atom models. To address this issue, coarse-grained models of RNA three-dimensional structures have been developed. In this chapter, we describe a graphical modeling based on the Leontis–Westhof exten

虚构的东西

Motif Discovery from CLIP Experiments, RNA-Binding Proteins, and several methods have been developed to meet the need of fast and efficient discovery of interaction motifs. Recent advances have increased the amount of data produced by experimental assays and there is no available method suitable for the analysis of all type of results.

Wernickes-area

Profiling of RNA Structure at Single-Nucleotide Resolution Using nextPARS, secondary structure of RNAs is central to understanding RNA function and evolution. RNA structure probing techniques coupled to high-throughput sequencing allow determining structural features of RNA molecules at transcriptome-wide scales. Our group recently developed a novel Illumina-based impleme

PANT

过滤

Using RNentropy to Detect Significant Variation in Gene Expression Across Multiple RNA-Seq or Singlhave been proposed to model and detect differential gene expression based on the comparison of transcript abundances across different samples. However, state-of-the-art methods for this task are usually designed for pairwise comparisons, that is, can identify significant variation of expression only