Titlebook: Computational Methods and Data Analysis for Metabolomics; Shuzhao Li Book 2020 Springer Science+Business Media, LLC, part of Springer Natu

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The Essential Toolbox of Data Science: Python, R, Git, and Docker,ization tool Docker. Proficiency in at least one programming language is required for data science. R is tied to a computing environment that focuses on statistics, in which many new algorithms in genomics and biomedicine are first published. Python has a root in system administration, and is a supe

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Using MetaboAnalyst 4.0 for Metabolomics Data Analysis, Interpretation, and Integration with Other interpretation, as well as integration with other omics data. This chapter first provides an introductory overview to the current MetaboAnalyst (version 4.0) with regards to its underlying design concepts and user interface structure. Subsequent sections describe three common metabolomics data anal

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Pathway Analysis for Targeted and Untargeted Metabolomics,lp place the experimental observations into relevant biological or disease context. This chapter provides an overview of the general concepts and common tools for pathway analysis, including Mummichog for untargeted metabolomics. Examples of pathway mapping, MetScape, and Mummichog are explained. Th

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Shuzhao LiIncludes cutting-edge methods and protocols.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from the experts