Hardcover. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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T�tulo: Computational Epigenomics and Epitranscriptomics (Hardcover)
Editor: Springer-Verlag New York Inc., New York, NY
Fecha de publicaci�n: 2023
Idioma: Ingl�s
ISBN 10: 1071629611
ISBN 13: 9781071629611
Encuadernaci�n: Hardcover
Estado: new

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Sinopsis

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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