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

S. Van Nuffel; C. Parmenter; D. J. Scurr; N. A. Russell; M. Zelzer

doi:10.1039/c5an01743b

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

S. Van Nuffel, C. Parmenter, D. J. Scurr, N. A. Russell, M. Zelzer^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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).

Original language	English
Pages (from-to)	90-95
Number of pages	6
Journal	Analyst
Volume	141
Issue number	1
DOIs	https://doi.org/10.1039/c5an01743b
Publication status	Published - 2016
Externally published	Yes

Keywords

ION MASS-SPECTROMETRY
CELLS
FILMS
INFORMATION

Access to Document

10.1039/c5an01743bLicence: CC BY

Cite this

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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).",

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AU - Russell, N. A.

AU - Zelzer, M.

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KW - FILMS

KW - INFORMATION

U2 - 10.1039/c5an01743b

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