en
Doctoral thesis
English

Development of computational tools to improve data-independent workflows for the characterization of proteins and metabolites by mass spectrometry

Defense date2015-12-09
Abstract

This thesis focuses on the design, implementation and benchmarking of various software tools aiming to improve the identification and quantification of complex protein digests and metabolites analyzed by LC-MS/MS. The solutions involve different steps in the workflow, from enhanced data acquisition to novel post-acquisition data processing strategies. A significant increase of peptide/protein identification rates was achieved by combining exclusion and inclusion lists in data-dependent acquisition. Data-independent acquisition schemes are examined, in particular, related algorithms and computational methods are discussed. A program was implemented to design and optimize different SWATH acquisition methods and the benefits of variable isolation windows are demonstrated for the profiling of proteomic and metabolic samples. A ranking algorithm was developed to assign low priority to fragment ions affected by interference during SWATH acquisition and the improvements for label-free quantification are illustrated. Finally, several demultiplexing approaches towards peptide identification by sequence database search of SWATH spectra were investigated.

eng
Keywords
  • Data-independent acquisition
  • Interference removal
  • Metabolomics
  • Proteomics
  • SWATH
  • Variable-precursor-isolation-window widths
Citation (ISO format)
BILBAO PENA, Aivett. Development of computational tools to improve data-independent workflows for the characterization of proteins and metabolites by mass spectrometry. 2015. doi: 10.13097/archive-ouverte/unige:80046
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Technical informations

Creation01/07/2016 4:18:00 PM
First validation01/07/2016 4:18:00 PM
Update time03/30/2023 10:38:47 AM
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