Simopoulos, Caitlin M.A., Figeys, Daniel and Lavallée-Adam, Mathieu (2022) Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies. In: Methods in Molecular Biology. Methods in Molecular Biology, 2456 . Humana Press Inc, New York, pp. 319-338. ISBN 978-1-0716-2123-3
Full text not available from this repository. (Request a copy)Abstract
Constant improvements in mass spectrometry technologies and laboratory workflows have enabled the proteomics investigation of biological samples of growing complexity. Microbiomes represent such complex samples for which metaproteomics analyses are becoming increasingly popular. Metaproteomics experimental procedures create large amounts of data from which biologically relevant signal must be efficiently extracted to draw meaningful conclusions. Such a data processing requires appropriate bioinformatics tools specifically developed for, or capable of handling metaproteomics data. In this chapter, we outline current and novel tools that can perform the most commonly used steps in the analysis of cutting-edge metaproteomics data, such as peptide and protein identification and quantification, as well as data normalization, imputation, mining, and visualization. We also provide details about the experimental setups in which these tools should be used.
| Item Type: | Book Section |
|---|---|
| Uncontrolled Keywords: | bioinformatics,computational biology,mass spectrometry,metaproteomics,microbiome,proteomics,quantification,software,statistics,molecular biology,genetics ,/dk/atira/pure/subjectarea/asjc/1300/1312 |
| Faculty \ School: | Faculty of Medicine and Health Sciences > Norwich Medical School |
| UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 23 Mar 2026 14:30 |
| Last Modified: | 23 Mar 2026 14:30 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/102561 |
| DOI: | 10.1007/978-1-0716-2124-0_22 |
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