Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques: A large-scale benchmarking study.

ABSTRACT: Today machine learning methods are commonly deployed for bacterial species identification using MALDI-TOF mass spectrometry data. However, most of the studies reported in literature only consider very traditional machine learning methods on small datasets that contain a limited number of species. In this paper we present benchmarking results on an unprecedented scale for a wide range of machine learning methods, using datasets that contain almost 100,000 spectra and more than 1000 different species. The size and the diversity of the data allow to compare three important identification scenarios that are often not distinguished in literature, i.e., identification for novel biological replicates, novel strains and novel species that are not present in the training data. The results demonstra

SUBMITTER: Mortier T 

PROVIDER: S-EPMC8649224 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature