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• W76055961 abstract "Proteins are involved in essentially any cellular process and constitute key players in the regulation of biological systems. The analysis of their abundance level, modification state and how they interact with each other is therefore indispensable for the precise understanding of biological mechanisms in a cell. The scope of this Ph.D. thesis focusses on novel computational methods that support analytical approaches for the identification and quantification of proteins. Liquid chromatography coupled to mass spectrometry (LC-MS) represents a very popular technique for the characterization of protein mixtures. Initially, proteins are digested into smaller peptide elements where the masses of the generated peptides are precisely measured by LC-MS. Subsequently, tandem mass spectrometry (MS/MS) determines the identity of selected peptides. In a high throughput mode, shotgun proteomics approaches have the potential to collect thousands of peptide identifications by repeated MS/MS analysis in the course of an LC-MS experiment. However, current problems in shotgun proteomics experiments include the identification of proteins at very low concentrations and the accurate quantification of their abundance changes across different LC-MS measurements. We address here the challenges of shotgun proteomics approaches through the development of a novel computational framework for the in-depth analysis of high mass precision LC-MS data. This thesis describes the software SuperHirn, which detects peptides independent of MS/MS information and tracks these across multiple measurements. Furthermore, we introduce the concept of the MasterMap, which constitutes a comprehensive repository for the storage of extracted and processed peptide signals. We illustrate the functionality of SuperHirn and the MasterMap in the MS/MS independent quantification and classification of protein abundance changes in complex biological samples. The convenience of the developed computational methodology is further illustrated by different applications addressing emerging topics in protein-centered biology. In a first example, we present a novel strategy for the quantitative analysis of protein-protein interactions. Based on peptide signals archived in a MasterMap, the presented results provide biological insights into the protein interaction network of the human forkhead transcription factor FoxO3A. In particular, the mechanistic" @default.
• W76055961 created "2016-06-24" @default.
• W76055961 creator A5054939918 @default.
• W76055961 date "2008-01-01" @default.
• W76055961 modified "2023-09-27" @default.
• W76055961 title "Novel computational techniques for quantitative mass spectrometry based proteomics" @default.
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