GHU Logo
The Great Heights University Library
Academic discovery, digital access, and research support

Computational Epigenomics and Epitranscriptomics [electronic resource] / edited by Pedro H. Oliveira.

Contributor(s): Material type: TextSeries: Methods in Molecular Biology ; 2624Publisher: New York, NY : Springer US : Imprint: Humana, 2023Edition: 1st ed. 2023Description: XI, 262 p. 65 illus., 61 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781071629628
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 572.865 23
LOC classification:
  • QH426-470
Online resources:
Contents:
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 (ψ) in RNA by HydraPsiSeq -- Analysis of RNA sequences and modifications using NASE -- Mapping of RNA modifications by direct Nanopore sequencing and JACUSA2.
In: Springer Nature eBookSummary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

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 (ψ) in RNA by HydraPsiSeq -- Analysis of RNA sequences and modifications using NASE -- Mapping of RNA modifications by direct Nanopore sequencing and JACUSA2.

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.

Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.

No reading system accessibility options actively disabled

Publisher contact for further accessibility information: accessibilitysupport@springernature.com

There are no comments on this title.

to post a comment.