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Principal coordinate analysis assisted chromatographic analysis of bacterial cell wall collection: a robust classification approach
Umeå universitet, Medicinska fakulteten, Molekylär Infektionsmedicin, Sverige (MIMS). Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten). Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR).
Umeå universitet, Medicinska fakulteten, Molekylär Infektionsmedicin, Sverige (MIMS). Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten). Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR).
2018 (engelsk)Inngår i: Analytical Biochemistry, ISSN 0003-2697, E-ISSN 1096-0309, Vol. 550, s. 8-14Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In the present work, Principal coordinate analysis (PCoA) is introduced to develop a robust model to classify the chromatographic data sets of peptidoglycan sample. PcoA captures the heterogeneity present in the data sets by using the dissimilarity matrix as input. Thus, in principle, it can even capture the subtle differences in the bacterial peptidoglycan composition and can provide a more robust and fast approach for classifying the bacterial collection and identifying the novel cell wall targets for further biological and clinical studies. The utility of the proposed approach is successfully demonstrated by analysing the two different kind of bacterial collections. The first set comprised of peptidoglycan sample belonging to different subclasses of Alphaproteobacteria. Whereas, the second set that is relatively more intricate for the chemometric analysis consist of different wild type Vibrio Cholerae and its mutants having subtle differences in their peptidoglycan composition. The present work clearly proposes a useful approach that can classify the chromatographic data sets of chromatographic peptidoglycan samples having subtle differences. Furthermore, present work clearly suggest that PCoA can be a method of choice in any data analysis workflow.

sted, utgiver, år, opplag, sider
Elsevier, 2018. Vol. 550, s. 8-14
Emneord [en]
Principal coordinate analysis, Classification, Peptidoglycans, Chromatography, Principal component analysis, Data heterogeneity
HSV kategori
Identifikatorer
URN: urn:nbn:se:umu:diva-150872DOI: 10.1016/j.ab.2018.04.008ISI: 000436056600002PubMedID: 29649471Scopus ID: 2-s2.0-85045282388OAI: oai:DiVA.org:umu-150872DiVA, id: diva2:1244378
Tilgjengelig fra: 2018-08-31 Laget: 2018-08-31 Sist oppdatert: 2018-08-31bibliografisk kontrollert

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