Multivariate analysis of 3D ToF-SIMS images: method validation and application to cultured neuronal networks

Van Nuffel, Sebastiaan; Parmenter, Christopher D.J.; Scurr, David J.; Russell, Noah A.; Zelzer, Mischa

Abstract

Advanced data analysis tools are crucial for the application of ToF-SIMS analysis to biological samples. Here, we demonstrate that by using a training set approach principal components analysis (PCA) can be performed on large 3D ToF-SIMS images of neuronal cell cultures. The method readily provides access to sample component information and significantly improves the images’ signal-to-noise ratio (SNR).

Citation

Van Nuffel, S., Parmenter, C. D., Scurr, D. J., Russell, N. A., & Zelzer, M. (in press). Multivariate analysis of 3D ToF-SIMS images: method validation and application to cultured neuronal networks. Analyst, 141(1), https://doi.org/10.1039/c5an01743b

• Journal Article Type: Article
• Acceptance Date: Nov 20, 2015
• Online Publication Date: Nov 20, 2015
• Deposit Date: Dec 11, 2015
• Publicly Available Date: Dec 11, 2015
• Journal: Analyst
• Print ISSN: 0003-2654
• Electronic ISSN: 1364-5528
• Publisher: Royal Society of Chemistry
• Peer Reviewed: Peer Reviewed
• Volume: 141
• Issue: 1
• DOI: https://doi.org/10.1039/c5an01743b
• Public URL: https://nottingham-repository.worktribe.com/output/765794
• Publisher URL: http://pubs.rsc.org/en/Content/ArticleLanding/2016/AN/C5AN01743B
• Related Public URLs: https://rdmc.nottingham.ac.uk/handle/internal/54
• Contract Date: Dec 11, 2015