书目名称 | Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry | 编辑 | Susmita Datta,Bart J. A. Mertens | 视频video | | 概述 | Presents an overview of distinct forms of mass spectrometry for different objectives and their associated statistical analysis from an internationally represented field of interdisciplinary contributo | 丛书名称 | Frontiers in Probability and the Statistical Sciences | 图书封面 |  | 描述 | .This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies..Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass spectrometry, time-of-flight data, and Fourier transform mass spectrometry are but a selection of the measurement platforms available to the modern analyst. Thus in practical | 出版日期 | Book 2017 | 关键词 | Bayesian; analysis; analytical chemistry; biochemistry; bioinformatics; biomarker; biostatistics; computer | 版次 | 1 | doi | https://doi.org/10.1007/978-3-319-45809-0 | isbn_softcover | 978-3-319-83377-4 | isbn_ebook | 978-3-319-45809-0Series ISSN 2624-9987 Series E-ISSN 2624-9995 | issn_series | 2624-9987 | copyright | Springer International Publishing Switzerland 2017 |
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