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An optimized comparative proteomic approach as a tool in neurodegenerative disease research

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-285912
  • Recent advances in proteomic technologies now allow unparalleled assessment of the molecular composition of a wide range of sample types. However, the application of such technologies and techniques should not be undertaken lightly. Here, we describe why the design of a proteomics experiment itself is only the first step in yielding high-quality, translatable results. Indeed, the effectiveness and/or impact of the majority of contemporary proteomics screens are hindered not by commonly considered technical limitations such as low proteomeRecent advances in proteomic technologies now allow unparalleled assessment of the molecular composition of a wide range of sample types. However, the application of such technologies and techniques should not be undertaken lightly. Here, we describe why the design of a proteomics experiment itself is only the first step in yielding high-quality, translatable results. Indeed, the effectiveness and/or impact of the majority of contemporary proteomics screens are hindered not by commonly considered technical limitations such as low proteome coverage but rather by insufficient analyses. Proteomic experimentation requires a careful methodological selection to account for variables from sample collection, through to database searches for peptide identification to standardised post-mass spectrometry options directed analysis workflow, which should be adjusted for each study, from determining when and how to filter proteomic data to choosing holistic versus trend-wise analyses for biologically relevant patterns. Finally, we highlight and discuss the difficulties inherent in the modelling and study of the majority of progressive neurodegenerative conditions. We provide evidence (in the context of neurodegenerative research) for the benefit of undertaking a comparative approach through the application of the above considerations in the alignment of publicly available pre-existing data sets to identify potential novel regulators of neuronal stability.zeige mehrzeige weniger

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Autor(en): Rachel A. Kline, Lena Lößlein, Dominic Kurian, Judit Aguilar Martí, Samantha L. Eaton, Felipe A. Court, Thomas H. Gillingwater, Thomas M. Wishart
URN:urn:nbn:de:bvb:20-opus-285912
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Medizinische Fakultät / Neurologische Klinik und Poliklinik
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Cells
ISSN:2073-4409
Erscheinungsjahr:2022
Band / Jahrgang:11
Heft / Ausgabe:17
Aufsatznummer:2653
Originalveröffentlichung / Quelle:Cells (2022) 11:17, 2653. https://doi.org/10.3390/cells11172653
DOI:https://doi.org/10.3390/cells11172653
Allgemeine fachliche Zuordnung (DDC-Klassifikation):6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Freie Schlagwort(e):data filtering; experimental design; neurodegeneration; pathway analysis; proteomics; systems biology
Datum der Freischaltung:23.08.2023
Datum der Erstveröffentlichung:26.08.2022
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International