A graphical user interface for a fast multivariate classification of MALDI-TOF MS data of pollen grains

  • The common characterization and identification of pollen is a time-consuming task that mainly relies on microscopic determination of the genus-specific pollen morphology. A variety of spectroscopic and spectrometric approaches have been proposed to develop a fast and reliable pollen identification using specific molecular information. Amongst them, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows a high potential for the successful investigation of such complex biological samples. Based on optimized MALDI sample preparation using conductive carbon tape, the application of multivariate statistics (e.g. principal components analysis, PCA) yields an enormous improvement concerning taxonomic classification of pollen species compared to common microscopic techniques. Since multivariate evaluation of the recorded mass spectra is of vital importance for classification, it’s helpful to implement the applied sequence of standard MatlabThe common characterization and identification of pollen is a time-consuming task that mainly relies on microscopic determination of the genus-specific pollen morphology. A variety of spectroscopic and spectrometric approaches have been proposed to develop a fast and reliable pollen identification using specific molecular information. Amongst them, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows a high potential for the successful investigation of such complex biological samples. Based on optimized MALDI sample preparation using conductive carbon tape, the application of multivariate statistics (e.g. principal components analysis, PCA) yields an enormous improvement concerning taxonomic classification of pollen species compared to common microscopic techniques. Since multivariate evaluation of the recorded mass spectra is of vital importance for classification, it’s helpful to implement the applied sequence of standard Matlab functions into a graphical user interface (GUI). In this presentation, a stand-alone application (GUI) is shown, which provides multiple functions to perform fast multivariate analysis on multiple datasets. The use of a GUI enables a first overview on the measured dataset, conducts spectral pretreatment and can give classification information based on HCA and PCA evaluation. Moreover, it can be used to improve fast spectral classification and supports the development of a simple routine method to identify pollen based on mass spectrometry.zeige mehrzeige weniger

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Metadaten
Autor*innen:Franziska Lauer
Koautor*innen:Sabrina Diehn, Steffen Weidner, Janina Kneipp
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2018
Organisationseinheit der BAM:6 Materialchemie
6 Materialchemie / 6.3 Strukturanalytik
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Sanitär- und Kommunaltechnik; Umwelttechnik
Freie Schlagwörter:GUI; MALDI; Pollen
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Chemie und Prozesstechnik / Chemische Charakterisierung und Spurenanalytik
Umwelt
Umwelt / Umwelt-Material-Interaktionen
Veranstaltung:12. Interdisziplinäres Doktorandenseminar, GDCh AK Prozessanalytik
Veranstaltungsort:BAM, AH, Berlin, Germany
Beginndatum der Veranstaltung:25.03.2018
Enddatum der Veranstaltung:27.03.2018
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:10.04.2018
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
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