Proteomics Data Analysis (Methods in Molecular Biology, 2361) 1st ed. 2021 Edition

ISBN 10: 1071616404 / ISBN 13: 9781071616406

Verlag: Humana, 2021

Beschreibung

Print on Demand.

Bestandsnummer des Verkäufers 379238250

Bibliografische Details

• Titel: Proteomics Data Analysis (Methods in Molecular Biology, 2361) 1st ed. 2021 Edition
• Verlag: Humana
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 1071616404
• ISBN-13: 9781071616406
• Einband: Hardcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. 

Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.

Chapter 16 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Von der hinteren Coverseite

This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. 

Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.