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• W1593741515 abstract "In recent years, the study of metabolomics and the use of metabolomics data to answer a variety of biological questions have been greatly increasing (Fan, Lane et al. 2004; Griffin 2006; Khoo and Al-Rubeai 2007; Lindon, Holmes et al. 2007; Lawton, Berger et al. 2008). While various techniques are available for analyzing this type of data (Bryan, Brennan et al. 2008; Scalbert, Brennan et al. 2009; Thielen, Heinen et al. 2009; Xia, Psychogios et al. 2009), the fundamental goal of the analysis is the same – to quickly and accurately identify detected molecules so that biological mechanisms and modes of action can be understood. Metabolomics analysis was long thought of as, and in many aspects still is, an instrumentation problem; the better and more accurate the instrumentation (LC/MS, GC/MS, NMR, CE, etc.) the better the resulting data which, in turn, facilitates data interpretation and, ultimately, the understanding of the biological relevance of the results." @default.
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• W1593741515 date "2012-02-10" @default.
• W1593741515 modified "2023-10-03" @default.
• W1593741515 title "Software Techniques for Enabling High-Throughput Analysis of Metabolomic Datasets" @default.
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• W1593741515 doi "https://doi.org/10.5772/31277" @default.
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