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Transcriptome Data Analysis

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31 August 2024
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This detailed volume presents a comprehensive exploration of the advances in transcriptomics, with a focus on methods and pipelines for transcriptome data analysis. In addition to well-established RNA sequencing (RNA-Seq) data analysis protocols, the chapters also examine specialized pipelines, such as multi-omics data integration and analysis, gene interaction network construction, single-cell trajectory inference, detection of structural variants, application of machine learning, and more. As part of the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that leads to best results in the lab. 

 

Authoritative and practical, Transcriptome Data Analysis serves as an ideal resource for educators and researchers looking to understand new developments in the field, learn usage of the protocols for transcriptome data analysis, and implement the tools or pipelines to address relevant problemsof their interest.

 

Chapter 4 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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    Product Details
    ISBN-13
    9781071638859
    Author
    Rajeev K. Azad
    Publisher
    Springer Nature B.V.
    Published
    31 August 2024
    Format
    Hardback

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    RRP: $394.90
    $388.98
    Ships in 3-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Transcriptome Data Analysis

    RRP: $394.90
    $388.98

    Description

    This detailed volume presents a comprehensive exploration of the advances in transcriptomics, with a focus on methods and pipelines for transcriptome data analysis. In addition to well-established RNA sequencing (RNA-Seq) data analysis protocols, the chapters also examine specialized pipelines, such as multi-omics data integration and analysis, gene interaction network construction, single-cell trajectory inference, detection of structural variants, application of machine learning, and more. As part of the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that leads to best results in the lab. 

     

    Authoritative and practical, Transcriptome Data Analysis serves as an ideal resource for educators and researchers looking to understand new developments in the field, learn usage of the protocols for transcriptome data analysis, and implement the tools or pipelines to address relevant problemsof their interest.

     

    Chapter 4 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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