Colony Fingerprint-Based Discrimination of Staphylococcus species with Machine Learning Approaches.

ABSTRACT: Detection and discrimination of bacteria are crucial in a wide range of industries, including clinical testing, and food and beverage production. Staphylococcus species cause various diseases, and are frequently detected in clinical specimens and food products. In particular, S. aureus is well known to be the most pathogenic species. Conventional phenotypic and genotypic methods for discrimination of Staphylococcus spp. are time-consuming and labor-intensive. To address this issue, in the present study, we applied a novel discrimination methodology called colony fingerprinting. Colony fingerprinting discriminates bacterial species based on the multivariate analysis of the images of microcolonies (referred to as colony fingerprints) with a size of up to 250 μm in diamet

SUBMITTER: Maeda Y 

PROVIDER: S-EPMC6163207 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature