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Updated: Jul 12, 2025

Subtyping of Campylobacter jejuni ssp. doylei Isolates Using Mass Spectrometry-based PhyloProteomics MSPP
Published on: October 30, 2016
Promising potential of machine learning-assisted MALDI-TOF MS as an effective detector for Streptococcus suis
Zhuohao Wang1,2,3,4, Yu Zhou1,2,3,4, Genglin Guo1,2,3,4
1College of Veterinary Medicine, Nanjing Agricultural University , Nanjing, China.
Importance:
To the best of our knowledge, this study reveals a strong correlation between mass spectra pattern and virulence phenotype among S. suis for the first time. In order to make the findings applicable and to excavate the intrinsic information in the spectra, the classifiers based on the machine learning algorithms were established, and RF (Random Forest)-based models have achieved an accuracy of over 90%. Overall, this study will pave the way for virulent SS2 (Streptococcus suis serotype 2) rapid detection, and the important findings on the association between genotype and mass spectrum may provide a new idea for the genotype-dependent detection of specific pathogens.
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