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Olivier Cloarec

Researcher at Imperial College London

Publications -  49
Citations -  8615

Olivier Cloarec is an academic researcher from Imperial College London. The author has contributed to research in topics: Gut flora & Computer science. The author has an hindex of 32, co-authored 46 publications receiving 8029 citations. Previous affiliations of Olivier Cloarec include University of London & Chinese Academy of Sciences.

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OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification†

TL;DR: In this paper, class-orthogonal variation can be exploited to augment classificaiton analysis (OPLS-DA) for the purpose of discriminant analysis, and the OPLS method can be used to augment classification.
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Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice

TL;DR: Multivariate statistical modeling of the spectra shows that the genetic predisposition of the 129S6 mouse to impaired glucose homeostasis and NAFLD is associated with disruptions of choline metabolism, and indicates that gut microbiota may play an active role in the development of insulin resistance.
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Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets.

TL;DR: The implementation of the statistical total correlation spectroscopy (STOCSY) analysis method with supervised pattern recognition and particularly orthogonal projection on latent structure-discriminant analysis (O-PLS-DA) offers a new powerful framework for analysis of metabonomic data.
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Pharmaco-metabonomic phenotyping and personalized drug treatment.

TL;DR: An alternative and conceptually new ‘pharmaco-metabonomic’ approach to personalizing drug treatment is described, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects.
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Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualization of biomarker changes in 1H NMR spectroscopic metabonomic studies.

TL;DR: The interpretation of chemometric models using combined back-scaled loading plots and variable weights demonstrates that this peak position variation can be handled successfully and also often provides additional information on the physicochemical variations in metabonomic data sets.