Computational Epigenomics and Epitranscriptomics [electronic resource] /
Computational Epigenomics and Epitranscriptomics [electronic resource] /
edited by Pedro H. Oliveira.
- 1st ed. 2023.
- XI, 262 p. 65 illus., 61 illus. in color. online resource.
- Methods in Molecular Biology, 2624 1940-6029 ; .
- Methods in Molecular Biology, 2624 .
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.
9781071629628
10.1007/978-1-0716-2962-8 doi
Epigenetics.
Biomathematics.
Epigenetics.
Mathematical and Computational Biology.
QH426-470
572.865
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.
9781071629628
10.1007/978-1-0716-2962-8 doi
Epigenetics.
Biomathematics.
Epigenetics.
Mathematical and Computational Biology.
QH426-470
572.865