• 식품기술
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• 제22권1호
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• pp.69-77
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• 2009

• 식품기술
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• 제23권2호
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• pp.238-256
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• 2010

• 식품기술
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• 제23권1호
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• pp.78-85
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• 2010

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 2007년도 Proceedings of The Convention
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• pp.31-31
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• 2007

• 통합자연과학논문집
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• 제11권3호
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• pp.161-164
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• 2018

Over the past decade, mass spectrometry-based metabolomics, especially two dimensional gas chromatography mass spectrometry (GCxGC/TOF-MS), has become a key analytical tool for metabolomics data because of its sensitivity and ability to analyze complex biological or biochemical sample. However, the need to reduce variations within/between experiments has been reported and methodological developments to overcome such problem has long been a critical issue. Along with methodological developments, developing reasonable performance measure has also been studied. Following four numerical measures have been typically used for comparison: sensitivity, specificity, receiver operating characteristic (ROC) curves, and positive predictive value (PPV). However, more recently, such measures are replaced with F1 score in many fields including metabolomics area without any carefulness of its validity. Thus, we want to investigate the validity of F1 score on two examples, with the goal of raising the awareness in choosing appropriate performance comparison measure. We noticed that F1 score itself, as a performance measure, was not good enough. Accordingly, we suggest that F1 score be supplemented with other performance measure such as specificity to improve its validity.

• Biomolecules & Therapeutics
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• 제25권6호
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• pp.559-568
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• 2017

Metabolomics has been used as a powerful tool for the analysis and quality assessment of the natural product (NP)-derived medicines. It is increasingly being used in the quality control and standardization of NP-derived medicines because they are composed of hundreds of natural compounds. The most common techniques that are used in metabolomics consist of NMR, GC-MS, and LC-MS in combination with multivariate statistical analyses including principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Currently, the quality control of the NP-derived medicines is usually conducted using HPLC and is specified by one or two indicators. To create a superior quality control framework and avoid adulterated drugs, it is necessary to be able to determine and establish standards based on multiple ingredients using metabolic profiling and fingerprinting. Therefore, the application of various analytical tools in the quality control of NP-derived medicines forms the major part of this review. $Veregen^{(R)}$ (Medigene AG, Planegg/Martinsried, Germany), which is the first botanical prescription drug approved by US Food and Drug Administration, is reviewed as an example that will hopefully provide future directions and perspectives on metabolomics technologies available for the quality control of NP-derived medicines.

• 한국자기공명학회논문지
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• 제22권3호
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• pp.46-53
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• 2018

NMR-based metabolomics needs various knowledge to elucidate metabolic perturbation such as NMR experiments, NMR spectrum processing, raw data processing, metabolite identification, statistical analysis, and metabolic pathway analysis regarding technical aspects. Among them, some concepts of raw data processing and multivariate analysis are not easy to understand but are important to correctly interpret metabolic profile. This article introduces NMR spectrum processing, raw data processing, and multivariate analysis.

• Mass Spectrometry Letters
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• 제11권2호
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• pp.17-24
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• 2020

Metabolomics has become an important research field with many areas of applications ranging from disease biomarker discovery to global biology systems study. A key step in metabolomics is to perform metabolome analysis to obtain quantitative information on metabolic changes among comparative samples. Mass spectrometry (MS) is widely used for highly sensitive detection of many different types of metabolites. In this review, we highlight some of the more commonly used MS techniques for metabolome analysis.

• Mass Spectrometry Letters
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• 제13권1호
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• pp.2-10
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• 2022

Metabolomics makes it possible to analyze the interrelationships between various signaling molecules based on the metabolic pathways involved by using high-resolution devices. This approach can also be used to obtain large-scale metabolic information to identify the relevant pathways for disease diagnosis and prognosis and search for potential biomarkers. In the fields of medicine and forensics, hair analysis is used to detect various metabolites in the body. Hair can be harvested readily in a noninvasive manner and is easier to transport and store than blood and urine. Another advantage from a forensic viewpoint is that hair reflects all the components of body fluids. In addition, because of the unique coating structure of hair, it can be used for measurements without changing or destroying its adsorbed components. In this review, the pretreatments for hair analysis, instrumental conditions and clinical applications are discussed. Especially, the clinical use of hair metabolomics in the diagnosis of various diseases and the limitations of the technique are described.

• 한국약용작물학회:학술대회논문집
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• 한국약용작물학회 2011년도 추계학술발표회
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• pp.90-91
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• 2011