Over het archief
Het OWA, het open archief van het Waterbouwkundig Laboratorium heeft tot doel alle vrij toegankelijke onderzoeksresultaten van dit instituut in digitale vorm aan te bieden. Op die manier wil het de zichtbaarheid, verspreiding en gebruik van deze onderzoeksresultaten, alsook de wetenschappelijke communicatie maximaal bevorderen.
Dit archief wordt uitgebouwd en beheerd volgens de principes van de Open Access Movement, en het daaruit ontstane Open Archives Initiative.
Basisinformatie over ‘Open Access to scholarly information'.
| one publication added to basket [381134] |
A universal tool for marine metazoan species identification: towards best practices in proteomic fingerprinting
Rossel, S.; Peters, J.; Charzinski, N.; Eichsteller, A.; Laakmann, S.; Neumann, H.; Martinez Arbizu, P. (2024). A universal tool for marine metazoan species identification: towards best practices in proteomic fingerprinting. NPG Scientific Reports 14(1): 1280. https://dx.doi.org/10.1038/s41598-024-51235-z
In: Scientific Reports (Nature Publishing Group). Nature Publishing Group: London. ISSN 2045-2322; e-ISSN 2045-2322, meer
|   |
| Auteurs | | Top |
- Rossel, S.
- Peters, J.
- Charzinski, N.
- Eichsteller, A.
|
- Laakmann, S.
- Neumann, H.
- Martinez Arbizu, P., meer
|
|
| Abstract |
Proteomic fingerprinting using MALDI-TOF mass spectrometry is a well-established tool for identifying microorganisms and has shown promising results for identification of animal species, particularly disease vectors and marine organisms. And thus can be a vital tool for biodiversity assessments in ecological studies. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1246 specimens and 198 species to test species identification in a diverse dataset. We also evaluated different specimen preparation and data processing approaches for machine learning and developed a workflow to optimize classification using random forest. Our results showed high success rates of over 90%, but we also found that the size of the reference library affects classification error. Additionally, we demonstrated the ability of the method to differentiate marine cryptic-species complexes and to distinguish sexes within species. |
IMIS is ontwikkeld en wordt gehost door het VLIZ.
