Pattern recognition methods and applications in biomedical magnetic resonance

By John C. Lindon, Edward C. Holmes, Jeremy K. Nicholson. 2001

403 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/67fcea98aef721b278c7bed6ed1b39bec3f6b3aa

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In Artificial Intelligence

In Computer Vision and Pattern Recognition

In Molecular Biology

Citations in the corpus

NMR-based metabolomic analysis of plants (2010, methodology): “More information on the background and application of those methods can be found in several excellent review”
Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics (2002, background): “First, it can be carried out on standard preparations of serum, plasma or urin”
Quantitative metabolic profiles of tomato flesh and seeds during fruit development: complementary analysis with ANN and PCA (2007, methodology): “To explore the metabolite multidimensional data set, two unsupervised statistical methods were used: PCA (Lindon et al., 2001) and the self-organizing map (SOM) algorithm (Kohonen, 2001) that is a particular application of ANN.”
Metabonomics: a platform for studying drug toxicity and gene function (2002, background): “So, each biofluid yields a characteristic 1 H-NMR spectroscopic fingerprint in which the spectral intensity distribution is determined by the relative concentrations of solutes, and in some cases by their intermolecular interaction”
Correlation between heat-shock protein induction and reduced metabolic condition in juvenile steelhead trout (Oncorhynchus mykiss) chronically exposed to elevated temperature (2003, methodology): “Pattern recognition methods are used to identify the subset of metabolites that respond most significantly to the stressor, thus providing a powerful approach for identifying novel metabolic biomarkers ( Lindon et al. 2001; Bundy et al. 2002).”
Gaussian binning: a new kernel-based method for processing NMR spectroscopic data for metabolomics (2008, methodology): “Further, nuclear magnetic resonance (NMR) spectroscopy of biofluids has been shown to be an effective method in metabolomics to identify variations in biological states (Lindon et al. 2001; Nicholson and Wilson 1989; Shockcor and Holmes 2002).”