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Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers

机译:用于NMR代谢组学研究分析的生物信息学工具着重于临床相关生物标志物的鉴定

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摘要

Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers.
机译:代谢组学是一种专注于代谢组学全球研究的系统生物学方法,在临床样品分析中具有巨大的潜力。在其他应用中,代谢组学可以绘制涉及疾病发病机制的生化变化的图谱,并提供机会以非侵入性的方式识别可以转化为早期治疗干预措施的诊断,预后和预测性生物标志物。特别是,通过核磁共振(NMR)进行的代谢组学研究具有同时检测并在结构上表征大量代谢成分的能力,即使它们的身份未知。对使用这种实验方法生成的数据进行分析需要应用统计和生物信息学工具来正确解释结果。这篇综述着重于针对临床应用的生物流体的代谢组学表征所涉及的不同步骤,从研究的设计到结果的生物学解释。特别强调处理和解释NMR数据所需的特定程序,重点是临床相关生物标志物的鉴定。

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