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Princeton University Library Catalog
Computational epigenomics and epitranscriptomics / edited by Pedro H. Oliveira.
New York, NY : Humana Press, 
xi, 262 pages : illustrations (some color) ; 26 cm.
Oliveira, Pedro H.
Methods in molecular biology (Clifton, N.J.) ; v. 2624.
[More in this series]
Springer protocols (Series)
[More in this series]
Methods in molecular biology, 1064-3745 ; 2624
This volume details state-of-the-art computational methods designed to manage, analyze, and generally leverage epigenomic and epitranscriptomic data. Chapters guide readers through fine-mapping and quantification of modifications, visual analytics, imputation methods, supervised analysis, and integrative approaches for single-cell data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Computational Epigenomics and Epitranscriptomics aims to provide an overview of epiomic protocols, making it easier for researchers to extract impactful biological insight from their data.
Includes bibliographical references and index.
DNA methylation data analysis using Msuite
Interactive DNA methylation arrays analysis with ShinyÉPICo
Predicting Chromatin Interactions from DNA Sequence using DeepC
Integrating single-cell methylome and transcriptome data with MAPLE
Quantitative comparison of multiple chromatin immunoprecipitation-sequencing (ChIP-seq) experiments with spikChIP
A Guide To MethylationToActivity: A Deep-Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes In Individual Tumors
DNA modification patterns filtering and analysis using DNAModAnnot
Methylome imputation by methylation patterns
Sequoia: a framework for visual analysis of RNA modifications from direct RNA sequencing data
Predicting pseudouridine sites with Porpoise
Pseudouridine Identification and Functional Annotation with PIANO
Analyzing mRNA epigenetic sequencing data with TRESS
Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores
Data Analysis Pipeline for Detection and Quantification of Pseudouridine ([psi]) in RNA by HydraPsiSeq
Analysis of RNA sequences and modifications using NASE
Mapping of RNA modifications by direct Nanopore sequencing and JACUSA2.
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Computational Epigenomics and Epitranscriptomics