Premium
Multivariate analysis of ToF‐SIMS data for biological applications
Author(s) -
Park JiWon,
Min Hyegeun,
Kim YoungPil,
Kyong Shon Hyun,
Kim Jinmo,
Moon Dae Won,
Lee Tae Geol
Publication year - 2009
Publication title -
surface and interface analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 90
eISSN - 1096-9918
pISSN - 0142-2421
DOI - 10.1002/sia.3049
Subject(s) - principal component analysis , biomolecule , secondary ion mass spectrometry , multivariate statistics , chemistry , biological system , characterization (materials science) , analytical chemistry (journal) , multivariate analysis , mass spectrometry , nanotechnology , computer science , materials science , chromatography , artificial intelligence , biology , machine learning
Abstract Applications of time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) were demonstrated, focusing on multivariate analysis (MVA) such as principal component analysis (PCA), principal component regression (PCR), and maximum autocorrelation factors (MAF). Three main categories are presented in this report: quantitative analysis of protein and chemical derivatives, surface characterization of chemical composition, and image‐based analysis in disease‐related tissues. The use of MVA in a ToF‐SIMS study showed improved data interpretation of chemicals or biomolecules on a surface, and consequently enabled the straightforward analysis of ToF‐SIMS data. Even on biological samples with high complexity, the MVA method effectively contributed to obtaining valuable information, including chemical distribution of biomolecules. It is anticipated that MVA with ToF‐SIMS data will be widely used for exploring biological studies in a reliable and simple way. Copyright © 2009 John Wiley & Sons, Ltd.