Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets.

By Olivier Cloarec, M. Dumas, A. Craig, R. H. Barton, Johan Trygg, Jane Hudson, C. Blancher, D. Gauguier, John C. Lindon, Edward C. Holmes and 1 more. Analytical Chemistry, 2005

857 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/24fa66c6bf700d6c791fbc65c2e5086249fb832b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. John C. Lindon
2. Jeremy K. Nicholson
3. Edward C. Holmes

In Biomedical Engineering

1. Jeremy K. Nicholson
2. Edward C. Holmes

In Molecular Biology

1. Jeremy K. Nicholson
2. Edward C. Holmes
3. John C. Lindon
4. David S. Wishart
5. Jacob G. Bundy
6. Ian A. Wilson
7. Mark R. Viant
8. James Kinross

Citations in the corpus

• Organization of GC/MS and LC/MS metabolomics data into chemical libraries (2010, background): “In that analysis, the multiple chemical shift peaks generated by a single molecule can be correlated across samples, grouped, and used to aid identification of detected molecules [13-16].”
• Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts (2007, methodology): “Multivariate spectroscopic data are typically analyzed using chemometric and pattern recognition techniques to extract latent metabolic information, and enable sample classification and biomarker discover”