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Elaine Holmes

Researcher at Imperial College London

Publications -  594
Citations -  66431

Elaine Holmes is an academic researcher from Imperial College London. The author has contributed to research in topics: Population & Microbiome. The author has an hindex of 119, co-authored 560 publications receiving 58975 citations. Previous affiliations of Elaine Holmes include McMaster University & Murdoch University.

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Host-Gut Microbiota Metabolic Interactions

TL;DR: A deeper understanding of the axes that physiologically connect the gut, liver, muscle, and brain are a prerequisite for optimizing therapeutic strategies to manipulate the gut microbiota to combat disease and improve health.
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'metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological nmr spectroscopic data

TL;DR: Metabonomics: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data by using NMR data from Xenobiotica.
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Metabonomics: a platform for studying drug toxicity and gene function

TL;DR: Metabonomics is a systems approach for studying in vivo metabolic profiles, which promises to provide information on drug toxicity, disease processes and gene function at several stages in the discovery-and-development process.
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Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts.

TL;DR: The main NMR spectroscopic applications in modern metabolic research are summarized, and detailed protocols for biofluid and tissue sample collection and preparation are provided, including the extraction of polar and lipophilic metabolites from tissues.
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Chemometrics in Metabonomics

TL;DR: An overview of how the underlying philosophy of chemometrics is integrated throughout metabonomic studies is provided, including the tools applied for linear modeling, for example, Statistical Experimental Design (SED), Principal Component Analysis (PCA), Partial least-squares (PLS), Orthogonal-PLS, and dynamic extensions thereof.