RNA bioinformatics

by Picardi, Ernesto

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Title Statements

Full title :RNA bioinformatics / edited by Ernesto Picardi.

Summary

This detailed book aims to provide an overview of novel bioinformatics resources for exploring diverse aspects of RNA biology. This edition focuses on methods dealing with non-coding RNA (miRNAs, circRNAs or lncRNAs), RNA modifications (m6A or RNA editing), single cell RNA-seq and statistical models to handle count data from RNA-seq experiments. The book also includes chapters based on the classical RNA bioinformatics methods, such as those for deciphering secondary and tertiary RNA structures; however, they are revised to take into account deep sequencing data. Finally, chapters describing methods to analyze RNA sequencing data from emerging third generation sequencing technologies that could provide interesting insights into the transcriptional process and its regulation are also included. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of expert implementation advice that encourages quality results. Comprehensive and up-to-date, RNA Bioinformatics, Second Edition serves as an ideal guide for researchers digging ever-deeper into the depths of the study of RNAs. The chapter 'RNA-Seq Data Analysis in Galaxy' is open access under a CC BY 4.0 license.

Edition Statements

Publication Date:2021
Edition:Second edition

Publication Statements

Publisher(s):Humana Press
Place of Publication:New York, NY
Language:eng
Publication Date:2021

Notes

Includes index.

The Physical Object

Description:1 online resource (xiv, 581 pages) : : illustrations (some color)

Edition Identifiers

ISBN:9781071613078, 1071613073
DOI:10.1007/978-1-0716-1307-8
oclc:on1246233291
LC Classification:QH324.2
Dewey Decimal:572.80285

Advanced Design of Structural RNAs Using RNARedPrint -- Modeling and Predicting RNA Three-Dimensional Structures -- Motif Discovery from CLIP Experiments -- Profiling of RNA Structure at Single-Nucleotide Resolution Using nextPARS -- RNA Framework for Assaying the Structure of RNAs by High-Throughput Sequencing -- Using RNentropy to Detect Significant Variation in Gene Expression across Multiple RNA-Seq or Single Cell RNA-Seq Samples -- Statistical Modeling of High Dimensional Counts -- QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing -- Summarizing RNA-Seq Data or Differentially Expressed Genes Using Gene Set, Network or Pathway Analysis -- Computational Analysis of circRNA Expression Data -- Differential Expression Analysis of Long Non-Coding RNAs -- Micro-RNA Quantification, Target Gene Identification, and Pathway Analysis -- In Silico Analysis of MicroRNA Sequencing Data -- RNA Editing Detection in HPC Infrastructures -- Identification of Genes Post-Transcriptionally Regulated from RNA-Seq: The Case Study of Liver Hepatocellular Carcinoma -- Computational Analysis of Single Cell RNA-Seq Data -- Normalization of Single-Cell RNA-Seq Data -- Dimensionality Red…