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Computational Epigenomics and Epitranscriptomics

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Cover of 'Computational Epigenomics and Epitranscriptomics'

Table of Contents

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    Book Overview
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    Chapter 1 DNA Methylation Data Analysis Using Msuite.
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    Chapter 2 Interactive DNA Methylation Array Analysis with ShinyÉPICo
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    Chapter 3 Predicting Chromatin Interactions from DNA Sequence Using DeepC
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    Chapter 4 Integrating Single-Cell Methylome and Transcriptome Data with MAPLE
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    Chapter 5 Quantitative Comparison of Multiple Chromatin Immunoprecipitation-Sequencing (ChIP-seq) Experiments with spikChIP
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    Chapter 6 A Guide to MethylationToActivity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors.
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    Chapter 7 DNA Modification Patterns Filtering and Analysis Using DNAModAnnot.
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    Chapter 8 Methylome Imputation by Methylation Patterns
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    Chapter 9 Sequoia: A Framework for Visual Analysis of RNA Modifications from Direct RNA Sequencing Data.
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    Chapter 10 Predicting Pseudouridine Sites with Porpoise.
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    Chapter 11 Pseudouridine Identification and Functional Annotation with PIANO.
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    Chapter 12 Analyzing mRNA Epigenetic Sequencing Data with TRESS.
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    Chapter 13 Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores.
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    Chapter 14 Data Analysis Pipeline for Detection and Quantification of Pseudouridine (ψ) in RNA by HydraPsiSeq.
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    Chapter 15 Analysis of RNA Sequences and Modifications Using NASE
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    Chapter 16 Mapping of RNA Modifications by Direct Nanopore Sequencing and JACUSA2.
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Title
Computational Epigenomics and Epitranscriptomics
Published by
Springer US, February 2023
DOI 10.1007/978-1-0716-2962-8
ISBNs
978-1-07-162961-1, 978-1-07-162962-8
Editors

H. Oliveira, Pedro

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