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

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Defense Thèse de doctorat : Univ. Genève, 2015 - Sc. 4872 - 2015/12/09
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.
Keywords Data-independent acquisitionInterference removalMetabolomicsProteomicsSWATHVariable-precursor-isolation-window widths
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URN: urn:nbn:ch:unige-800462
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Research groups Spectrométrie de masse du vivant
Proteome Informatics Group
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BILBAO PENA, Aivett. Development of computational tools to improve data-independent workflows for the characterization of proteins and metabolites by mass spectrometry. Université de Genève. Thèse, 2015. https://archive-ouverte.unige.ch/unige:80046

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Deposited on : 2016-01-25

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