Proteomics Data Analysis (Paperback, 1st ed. 2021)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Methods in Molecular Biology, 2361
Release date:	July 2022
First published:	2021
Editors:	Daniela Cecconi
Dimensions:	254 x 178mm (L x W)
Format:	Paperback
Pages:	326
Edition:	1st ed. 2021
ISBN-13:	978-1-07-161643-7
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Chemistry > General Books > Science & Mathematics > Biology, life sciences > Molecular biology Books > Science & Mathematics > Biology, life sciences > Biochemistry > Proteins
LSN:	1-07-161643-9
Barcode:	9781071616437

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