Boosting identification of microsporidian spores originating from different hosts: single-cell Raman spectroscopy combined with self-attention mechanism-driven convolutional neural network.

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Title: Boosting identification of microsporidian spores originating from different hosts: single-cell Raman spectroscopy combined with self-attention mechanism-driven convolutional neural network.
Authors: Xue M; School of Electronic Engineering and Intelligentization, Dongguan University of Technology, Dongguan, Guangdong, 523808, China.; College of Physics and Technology, Guangxi Normal University & University Engineering Research Center of Advanced Functional Materials and Intelligent Sensing, Guilin, Guangxi, 541004, China., Wang G; Institute of Eco-Environmental Research, Guangxi Academy of Sciences, Nanning, Guangxi, 530007, China., Sun Y; School of Electronic Engineering and Intelligentization, Dongguan University of Technology, Dongguan, Guangdong, 523808, China., Huang X; Guangxi Academy of Sericultural Sciences, Nanning, Guangxi, 530007, China., Hu J; College of Physics and Technology, Guangxi Normal University & University Engineering Research Center of Advanced Functional Materials and Intelligent Sensing, Guilin, Guangxi, 541004, China., Li Y; College of Physics and Technology, Guangxi Normal University & University Engineering Research Center of Advanced Functional Materials and Intelligent Sensing, Guilin, Guangxi, 541004, China. yuanpengli@gxnu.edu.cn., Yuan Y; School of Electronic Engineering and Intelligentization, Dongguan University of Technology, Dongguan, Guangdong, 523808, China. yufengyuan@dgut.edu.cn.
Source: Analytical and bioanalytical chemistry [Anal Bioanal Chem] 2026 Jul 25. Date of Electronic Publication: 2026 Jul 25.
Publication Type: Journal Article
Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101134327 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1618-2650 (Electronic) Linking ISSN: 16182642 NLM ISO Abbreviation: Anal Bioanal Chem Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1618-2650
DOI:10.1007/s00216-026-06695-9