Accurate Raman indicators of protein synthesis through sparse classification

Nicolas Pavillon; Nicholas Smith

doi:10.1117/12.2609775

2 March 2022 Accurate Raman indicators of protein synthesis through sparse classification

Nicolas Pavillon, Nicholas Smith

Author Affiliations +

Proceedings Volume 11957, Biomedical Vibrational Spectroscopy 2022: Advances in Research and Industry; 1195702 (2022) https://doi.org/10.1117/12.2609775
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

Raman spectroscopy (RS) has the ability to retrieve in a non-invasive way molecular information from cells and tissues, allowing the detection of various biological responses. It often relies on multivariate analysis to detect the changes of interest. We show here how regularized methods can improve the accuracy and stability of detection in the context of single-cell measurements for the detection of inflammation, or different phenotypes. We then use protein synthesis as a case study to assess which Raman bands are the most significant, and find that small bands outside of the main Raman regions are often more accurate for detection.

Conference Presentation

Citation Download Citation

Nicolas Pavillon and Nicholas Smith "Accurate Raman indicators of protein synthesis through sparse classification", Proc. SPIE 11957, Biomedical Vibrational Spectroscopy 2022: Advances in Research and Industry, 1195702 (2 March 2022); https://doi.org/10.1117/12.2609775

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