GlAIcomics: a deep neural network classifier for spectroscopy-augmented mass spectrometric glycans data

• Thomas Barillot,
• Baptiste Schindler,
• Baptiste Moge,
• Elisa Fadda,
• Franck Lépine and
• Isabelle Compagnon

Beilstein J. Org. Chem. 2023, 19, 1825–1831, doi:10.3762/bjoc.19.134

• intelligence in combination with spectroscopy-augmented mass spectrometry for carbohydrates sequencing and glycomics applications. Keywords: Bayesian neural network; deep learning; glycomics; IR; spectroscopy; Introduction DNA and protein sequencing technologies that aim at determining the structure of a

• spectra. We then benchmarked its discrimination capabilities with a mixture of hexosamines and other molecular spectra: the Bayesian neural network architecture offers an access to the model reliability (through its epistemic error) when it comes to classify the spectra and could be used to discriminate