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Computational Epigenomics and Epitranscriptomics
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Computational Epigenomics and Epitranscriptomics

2023 ed.

Book Details

Format Hardback or Cased Book
ISBN-10 1071629611
ISBN-13 9781071629611
Edition 2023 ed.
Publisher Springer-Verlag New York Inc.
Imprint Springer-Verlag New York Inc.
Country of Manufacture GB
Country of Publication GB
Publication Date Feb 2nd, 2023
Print length 262 Pages
Weight 708 grams
Dimensions 18.50 x 26.30 x 2.80 cms
Ksh 32,400.00
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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.

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.


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