Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.bbrc.2018.04.076
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dc.titleSphingolipidomics analysis of large clinical cohorts. Part 1: Technical notes and practical considerations
dc.contributor.authorChew, Wee Siong
dc.contributor.authorSeow, Wei Lun
dc.contributor.authorChong, Joyce R
dc.contributor.authorLai, Mitchell KP
dc.contributor.authorTorta, Federico
dc.contributor.authorWenk, Markus R
dc.contributor.authorHerr, Deron R
dc.date.accessioned2020-08-21T05:22:00Z
dc.date.available2020-08-21T05:22:00Z
dc.date.issued2018-10-07
dc.identifier.citationChew, Wee Siong, Seow, Wei Lun, Chong, Joyce R, Lai, Mitchell KP, Torta, Federico, Wenk, Markus R, Herr, Deron R (2018-10-07). Sphingolipidomics analysis of large clinical cohorts. Part 1: Technical notes and practical considerations. BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS 504 (3) : 596-601. ScholarBank@NUS Repository. https://doi.org/10.1016/j.bbrc.2018.04.076
dc.identifier.issn0006291X
dc.identifier.issn10902104
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/173261
dc.description.abstract© 2018 Elsevier Inc. Lipids comprise an exceptionally diverse class of bioactive macromolecules. While quantitatively abundant lipid species serve fundamental roles in cell structure and energy metabolism, thousands of structurally-distinct, quantitatively minor species may serve as important regulators of cellular processes. Historically, a complete understanding of the biological roles of these lipids has been limited by a lack of sensitive, discriminating analytical techniques. The class of sphingolipids alone, for example, is known to consist of over 600 different confirmed species, but is likely to include tens of thousands of metabolites with potential biological significance. Advances in mass spectrometry (MS) have improved the throughput and discrimination of lipid analysis, allowing for the determination of detailed lipid profiles in large cohorts of clinical samples. Databases emerging from these studies will provide a rich resource for the identification of novel biomarkers and for the discovery of potential drug targets, analogous to that of existing genomics databases. In this review, we will provide an overview of the field of sphingolipidomics, and will discuss some of the challenges and considerations facing the generation of robust lipidomics databases.
dc.language.isoen
dc.publisherACADEMIC PRESS INC ELSEVIER SCIENCE
dc.sourceElements
dc.subjectScience & Technology
dc.subjectLife Sciences & Biomedicine
dc.subjectBiochemistry & Molecular Biology
dc.subjectBiophysics
dc.subjectSphingolipid
dc.subjectLipidomics
dc.subjectMass spectrometry
dc.subjectSphingomyelin
dc.subjectCeramide
dc.subjectSphingosine 1-phosphate
dc.subjectTANDEM MASS-SPECTROMETRY
dc.subjectQUANTITATIVE-ANALYSIS
dc.subjectMETABONOMIC ANALYSIS
dc.subjectHIGH-THROUGHPUT
dc.subjectBLOOD-PLASMA
dc.subjectHUMAN URINE
dc.subjectHPLC-MS
dc.subjectLIPIDS
dc.subjectMETABOLOMICS
dc.subjectEXTRACTION
dc.typeArticle
dc.date.updated2020-06-17T04:41:40Z
dc.contributor.departmentBIOCHEMISTRY
dc.contributor.departmentPHARMACOLOGY
dc.description.doi10.1016/j.bbrc.2018.04.076
dc.description.sourcetitleBIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
dc.description.volume504
dc.description.issue3
dc.description.page596-601
dc.published.statePublished
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