Computational Methods for Understanding Mass Spectrometry-Based Shotgun Proteomics Data

Computational Methods for Understanding Mass Spectrometry-Based Shotgun Proteomics Data
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Book Synopsis Computational Methods for Understanding Mass Spectrometry-Based Shotgun Proteomics Data by : Pavel Sinitcyn

Download or read book Computational Methods for Understanding Mass Spectrometry-Based Shotgun Proteomics Data written by Pavel Sinitcyn and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational proteomics is the data science concerned with the identification and quantification of proteins from high-throughput data and the biological interpretation of their concentration changes, posttranslational modifications, interactions, and subcellular localizations. Today, these data most often originate from mass spectrometry-based shotgun proteomics experiments. In this review, we survey computational methods for the analysis of such proteomics data, focusing on the explanation of the key concepts. Starting with mass spectrometric feature detection, we then cover methods for the identification of peptides. Subsequently, protein inference and the control of false discovery rates are highly important topics covered. We then discuss methods for the quantification of peptides and proteins. A section on downstream data analysis covers exploratory statistics, network analysis, machine learning, and multiomics data integration. Finally, we discuss current developments and provide an outlook on what the near future of computational proteomics might bear.


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