Feature extraction for proteomics imaging mass spectrometry data

DOI10.1214/15-AOAS870zbMath1397.62475arXiv1410.1630OpenAlexW2281957915MaRDI QIDQ262375

Inge Koch, Peter Hoffmann, Stephan Meding, Lyron J. Winderbaum, Ove J. R. Gustafsson

Publication date: 29 March 2016

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1410.1630

zbMATH Keywords

binary datahigh-dimensionalMALDI-IMSmass spectrometry dataproteomicsunsupervised feature extraction

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Image analysis in multivariate analysis (62H35)

Uses Software

• KernSmooth

Cites Work

• Statistical methods for proteomic biomarker discovery based on feature extraction or functional modeling approaches
• Liquid chromatography mass spectrometry-based proteomics: biological and technological as\-pects
• Integral representation with weights. II: Division and interpolation
• Wavelet-based Functional Mixed Models
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