<p>A combined machine learning and glycomics analysis for the identification and discrimination of plant gum species used in historical artworks</p>

Narasimhan Balakrishnan; Amra Aksamija; Clara Granzotto; Kenneth Sutherland; Neda Bagheri

doi:10.7490/f1000research.1118291.1

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Balakrishnan N, Aksamija A, Granzotto C et al. A combined machine learning and glycomics analysis for the identification and discrimination of plant gum species used in historical artworks [version 1; not peer reviewed]. F1000Research 2020, 9(ISCB Comm J):1067 (poster) (https://doi.org/10.7490/f1000research.1118291.1)

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A combined machine learning and glycomics analysis for the identification and discrimination of plant gum species used in historical artworks

Narasimhan Balakrishnan¹, Amra Aksamija, Clara Granzotto, Kenneth Sutherland, Neda Bagheri

Published 30 Aug 2020 (https://doi.org/10.7490/f1000research.1118291.1)

Author Affiliations

¹ Northwestern University, USA

Copyright © 2020 Balakrishnan N et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 30 Aug 2020

A combined machine learning and glycomics analysis for the identification and discrimination of plant gum species used in historical artworks
[version 1; not peer reviewed]

Narasimhan Balakrishnan¹, Amra Aksamija, Clara Granzotto, Kenneth Sutherland, Neda Bagheri

Author Affiliations

¹ Northwestern University, USA

Presented at

28th International Conference on Intelligent Systems for Molecular Biology (ISMB) 2020

Competing Interests

No competing interests were disclosed

Keywords

Machine learning, mass spectrometry

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