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dc.contributor.authorRaja, Ganesan-
dc.contributor.authorJung, Youngmi-
dc.contributor.authorJung, Sang Hoon-
dc.contributor.authorKim, Tae-Jin-
dc.date.accessioned2024-01-19T16:02:25Z-
dc.date.available2024-01-19T16:02:25Z-
dc.date.created2021-09-02-
dc.date.issued2020-12-
dc.identifier.issn1359-5113-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/117769-
dc.description.abstractNuclear magnetic resonance (NMR) spectroscopy acts as the best tool that can be used in tissue engineering scaffolds to investigate unknown metabolites. Moreover, metabolomics is a systems approach for examining in vivo and in vitro metabolic profiles, which promises to provide data on cancer metabolic alterations. However, metabolomic profiling allows for the activity of small molecules and metabolic alterations to be measured. Furthermore, metabolic profiling also provides high-spectral resolution, which can then be linked to potential metabolic relationships. An altered metabolism is a hallmark of cancer that can control many malignant properties to drive tumorigenesis. Metabolite targeting and metabolic engineering contribute to carcinogenesis by proliferation, and metabolic differentiation. The resulting the metabolic differences are examined with traditional chemometric methods such as principal component analysis (PCA), and partial least squares-discriminate analysis (PLS-DA). In this review, we examine NMR-based activity metabolomic platforms that can be used to analyze various fluxomics and for multivariant statistical analysis in cancer. We also aim to provide the reader with a basic understanding of NMR spectroscopy, cancer metabolomics, target profiling, chemometrics, and multifunctional tools for metabolomics discrimination, with a focus on metabolic phenotypic diversity for cancer therapeutics.-
dc.languageEnglish-
dc.publisherELSEVIER SCI LTD-
dc.subjectPLANT-CELL CULTURES-
dc.subjectPATTERN-RECOGNITION-
dc.subjectSPECTROSCOPIC DATA-
dc.subjectDATA NORMALIZATION-
dc.subjectTECHNIQUES LESSONS-
dc.subjectBLADDER-CANCER-
dc.subjectNMR-SPECTRA-
dc.subjectIDENTIFICATION-
dc.subjectC-13-
dc.subjectH-1-
dc.titleH-1-NMR-based metabolomics for cancer targeting and metabolic engineering -A review-
dc.typeArticle-
dc.identifier.doi10.1016/j.procbio.2020.08.023-
dc.description.journalClass1-
dc.identifier.bibliographicCitationPROCESS BIOCHEMISTRY, v.99, pp.112 - 122-
dc.citation.titlePROCESS BIOCHEMISTRY-
dc.citation.volume99-
dc.citation.startPage112-
dc.citation.endPage122-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000596423400003-
dc.identifier.scopusid2-s2.0-85090333351-
dc.relation.journalWebOfScienceCategoryBiochemistry & Molecular Biology-
dc.relation.journalWebOfScienceCategoryBiotechnology & Applied Microbiology-
dc.relation.journalWebOfScienceCategoryEngineering, Chemical-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaBiotechnology & Applied Microbiology-
dc.relation.journalResearchAreaEngineering-
dc.type.docTypeReview-
dc.subject.keywordPlusPLANT-CELL CULTURES-
dc.subject.keywordPlusPATTERN-RECOGNITION-
dc.subject.keywordPlusSPECTROSCOPIC DATA-
dc.subject.keywordPlusDATA NORMALIZATION-
dc.subject.keywordPlusTECHNIQUES LESSONS-
dc.subject.keywordPlusBLADDER-CANCER-
dc.subject.keywordPlusNMR-SPECTRA-
dc.subject.keywordPlusIDENTIFICATION-
dc.subject.keywordPlusC-13-
dc.subject.keywordPlusH-1-
dc.subject.keywordAuthorCancer-
dc.subject.keywordAuthorMetabolomics-
dc.subject.keywordAuthorMetabolic engineering-
dc.subject.keywordAuthorTarget profiling-
dc.subject.keywordAuthorSoftware-
dc.subject.keywordAuthorTherapeutics-
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