RNA Bioinformatics

1. Front Matter

   Pages i-xiv

   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

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.

• Computational biology
• RNA biology
• RNA-Seq data
• Database resources
• Non-coding RNAs
• RNA modifications

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

  Ernesto Picardi

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