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RNA Bioinformatics

  • Book
  • © 2021

Overview

Editors:
  1. Ernesto Picardi

    1. Dipartimento Di Bioscienze Biotecnologie E Biofarmaceutica, Università degli Studi di Bari Aldo Moro, Bari, Italy

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  • Includes cutting-edge techniques
  • Provides step-by-step detail essential for reproducible results
  • Contains key implementation from the experts

Part of the book series: Methods in Molecular Biology (MIMB, volume 2284)

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Table of contents (32 protocols)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Advanced Design of Structural RNAs Using RNARedPrint

    • Yann Ponty, Stefan Hammer, Hua-Ting Yao, Sebastian Will
    Pages 1-15

  3. Modeling and Predicting RNA Three-Dimensional Structures

    • Vladimir Reinharz, Roman Sarrazin-Gendron, Jérôme Waldispühl
    Pages 17-42

  4. Motif Discovery from CLIP Experiments

    • Marco Pietrosanto, Gabriele Ausiello, Manuela Helmer-Citterich
    Pages 43-50

  5. Profiling of RNA Structure at Single-Nucleotide Resolution Using nextPARS

    • Uciel Chorostecki, Jesse R. Willis, Ester Saus, Toni Gabaldon
    Pages 51-62Open Access

  6. RNA Framework for Assaying the Structure of RNAs by High-Throughput Sequencing

    • Tycho Marinus, Danny Incarnato
    Pages 63-76

  7. Using RNentropy to Detect Significant Variation in Gene Expression Across Multiple RNA-Seq or Single-Cell RNA-Seq Samples

    • Federico Zambelli, Giulio Pavesi
    Pages 77-96

  8. Statistical Modeling of High Dimensional Counts

    • Michael I. Love
    Pages 97-134

  9. QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing

    • Ramya Gamini, Reiko Nakashima, Wen He, Chi Zhang, Ying Huang, Ying Zhang et al.
    Pages 135-145

  10. Summarizing RNA-Seq Data or Differentially Expressed Genes Using Gene Set, Network, or Pathway Analysis

    • Enrica Calura, Paolo Martini
    Pages 147-179

  11. Computational Analysis of circRNA Expression Data

    • Giulio Ferrero, Nicola Licheri, Michele De Bortoli, Raffaele A. Calogero, Marco Beccuti, Francesca Cordero
    Pages 181-192

  12. Differential Expression Analysis of Long Noncoding RNAs

    • Qian Li, Xuefeng Wang
    Pages 193-205

  13. Micro-RNA Quantification, Target Gene Identification, and Pathway Analysis

    • Gabriele Sales, Enrica Calura
    Pages 207-229

  14. In Silico Analysis of Micro-RNA Sequencing Data

    • Ernesto Aparicio-Puerta, Bastian Fromm, Michael Hackenberg, Marc K. Halushka
    Pages 231-251

  15. RNA Editing Detection in HPC Infrastructures

    • Claudio Lo Giudice, Luigi Mansi, Tiziano Flati, Silvia Gioiosa, Giovanni Chillemi, Pietro Libro et al.
    Pages 253-270

  16. Identification of Genes Post-Transcriptionally Regulated from RNA-seq: The Case Study of Liver Hepatocellular Carcinoma

    • Stefano de Pretis, Mattia Furlan, Mattia Pelizzola
    Pages 271-287

  17. Computational Analysis of Single-Cell RNA-Seq Data

    • Luca Alessandrì, Francesca Cordero, Marco Beccuti, Maddalena Arigoni, Raffaele A. Calogero
    Pages 289-301

  18. Normalization of Single-Cell RNA-Seq Data

    • Davide Risso
    Pages 303-329

  19. Dimensionality Reduction of Single-Cell RNA-Seq Data

    • George C. Linderman
    Pages 331-342

  20. Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview

    • Shaked Slovin, Annamaria Carissimo, Francesco Panariello, Antonio Grimaldi, Valentina Bouché, Gennaro Gambardella et al.
    Pages 343-365
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Keywords

About this book

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.

Editors and Affiliations

  • Dipartimento Di Bioscienze Biotecnologie E Biofarmaceutica, Università degli Studi di Bari Aldo Moro, Bari, Italy

    Ernesto Picardi

Bibliographic Information

  • Book Title: RNA Bioinformatics

  • Editors: Ernesto Picardi

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-0716-1307-8

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2021

  • Hardcover ISBN: 978-1-0716-1306-1Published: 10 April 2021

  • Softcover ISBN: 978-1-0716-1309-2Published: 10 April 2022

  • eBook ISBN: 978-1-0716-1307-8Published: 09 April 2021

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 2

  • Number of Pages: XIV, 581

  • Number of Illustrations: 25 b/w illustrations, 178 illustrations in colour

  • Topics: Biochemistry, general, Bioinformatics

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