MALDI-TOF mass spectrometry combined with machine learning algorithms to identify protein profiles related to malaria infection in human sera from Côte d’Ivoire
MALDI-TOF MS combined with ML might be applied for detection of protein profiles related to P. falciparum malaria infection in human serum samples. Additional research is warranted for further optimization such as specific biomarkers detection or using other ML models.
Authors
- Issa Sy (ORCID: https://orcid.org/0000-0001-9103-8861)
- Famoussa Koné (ORCID: https://orcid.org/0000-0002-1970-5161)
- Lucie Conrad
- Kigbafori D. Silué (ORCID: https://orcid.org/0000-0003-1003-9294)
- Jean T. Coulibaly (ORCID: https://orcid.org/0000-0002-3626-6068)
- Sören L. Becker (ORCID: https://orcid.org/0000-0003-3634-8802)
- Brama Koné (ORCID: https://orcid.org/0000-0001-9624-0647)
Institutions
- Swiss Tropical and Public Health Institute (CH)
- University of Basel (CH)
- Université Pelefero Gon Coulibaly (CI)
- Swiss Centre for Scientific Research (CI)
- Institute of Medical Microbiology and Hygiene (DE)
- Helmholtz Institute for Pharmaceutical Research Saarland (DE)
- Université Félix Houphouët-Boigny (CI)
- Saarland University (DE)
Publication Details
- Journal
- Malaria Journal
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1186/s12936-025-05362-1
- Citations
- 3
- Primary Topic
- Bacterial Identification and Susceptibility Testing
- Type
- article
- Field-Weighted Citation Impact
- 3.96
Funders
- Universität des Saarlandes