{"product_id":"computational-epigenomics-and-epitranscriptomics-9781071629642","title":"Computational Epigenomics and Epitranscriptomics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e1. DNA methylation data analysis using Msuite\u003c\/p\u003e  \u003cp\u003eXiaojian Liu, Pengxiang Yuan, and Kun Sun\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e2. Interactive DNA methylation arrays analysis with ShinyÉPICo\u003c\/p\u003e  \u003cp\u003eOctavio Morante-Palacios\u003csup\u003e\u003c\/sup\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e3. Predicting Chromatin Interactions from DNA Sequence using DeepC\u003c\/p\u003e  \u003cp\u003eRon Schwessinger\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e4. Integrating single-cell methylome and transcriptome data with MAPLE\u003c\/p\u003e  \u003cp\u003eYasin Uzun, Hao Wu, and Kai Tan\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e5. Quantitative comparison of multiple chromatin immunoprecipitation-sequencing (ChIP-seq) experiments with spikChIP\u003c\/p\u003e  Enrique Blanco, Cecilia Ballaré, Luciano Di Croce, and Sergi Aranda\u003csup\u003e\u003c\/sup\u003e\u003cp\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e6. A Guide To MethylationToActivity: A Deep-Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes In Individual Tumors\u003c\/p\u003e  \u003cp\u003eKarissa Dieseldorff Jones, Daniel Putnam, Justin Williams, and Xiang Chen\u003csup\u003e\u003c\/sup\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e7. DNA modification patterns filtering and analysis using DNAModAnnot\u003c\/p\u003e  \u003cp\u003eAlexis Hardy, Sandra Duharcourt, and Matthieu Defrance\u003csup\u003e\u003c\/sup\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e8. Methylome imputation by methylation patterns\u003c\/p\u003e  \u003cp\u003eYa-Ting Chang, Ming-Ren Yen, and Pao-Yang Chen\u003csup\u003e\u003c\/sup\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e9. Sequoia: a framework for visual analysis of RNA modifications from direct RNA sequencing data\u003c\/p\u003e  \u003cp\u003eRatanond Koonchanok, Swapna Vidhur Daulatabad, Khairi Reda, and Sarath Chandra Janga\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e10. Predicting pseudouridine sites with Porpoise\u003c\/p\u003e  \u003cp\u003eXudong Guo, Fuyi Li, and Jiangning Song\u003csup\u003e\u003c\/sup\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e11. Pseudouridine Identification and Functional Annotation with PIANO\u003c\/p\u003e  \u003cp\u003eJiahui Yao, Cuiyueyue Hao, Kunqi Chen, Jia Meng, and Bowen Song\u003csup\u003e\u003c\/sup\u003e\u003c\/p\u003e  \u003cp\u003e\u003csup\u003e \u003c\/sup\u003e\u003c\/p\u003e  12. Analyzing mRNA epigenetic sequencing data with TRESS\u003cp\u003e\u003c\/p\u003e  \u003cp\u003eZhenxing Guo, Andrew M. Shafik, Peng Jin, Zhijin Wu, and Hao Wu\u003c\/p\u003e  \u003cp\u003e\u003csup\u003e \u003c\/sup\u003e\u003c\/p\u003e  \u003cp\u003e13. Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores\u003c\/p\u003e  \u003cp\u003eLuca Cozzuto, Anna Delgado-Tejedor, Toni Hermoso Pulido, Eva Maria Novoa, \u003c\/p\u003e  \u003cp\u003eand Julia Ponomarenko\u003c\/p\u003e   \u003cp\u003e\u003c\/p\u003e  14. Data Analysis Pipeline for Detection and Quantification of Pseudouridine (ψ) in RNA by HydraPsiSeq Florian Pichot, Virginie Marchand, Mark Helm, and Yuri Motorin \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e15. Analysis of RNA sequences and modifications using NASE\u003c\/p\u003e  \u003cp\u003eSamuel Wein\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e16. Mapping of RNA modifications by direct Nanopore sequencing and JACUSA2\u003c\/p\u003e  \u003cp\u003eAmina Lemsara, Christoph Dieterich, and Isabel Naarmann-de Vries\u003c\/p\u003e","brand":"Springer-Verlag New York Inc.","offers":[{"title":"Default Title","offer_id":52090796343639,"sku":"9781071629642","price":98.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781071629642.jpg?v=1762273491","url":"https:\/\/bookcurl.com\/products\/computational-epigenomics-and-epitranscriptomics-9781071629642","provider":"Book Curl","version":"1.0","type":"link"}