Dealing with the unknown: Metabolomics and Metabolite Atlases |
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Authors: | Benjamin P Bowen Trent R Northen |
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Institution: | (1) Virginia Bioinformatics Institute, Washington St. 0477, Blacksburg, VA 24061, USA;(2) Comprehensive Cancer Center, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA;(3) School of Computer Science and Manchester Centre for Integrative Systems Biology, The University of Manchester, 131 Princess St, Manchester, M1 7DN, UK;(4) Department of Cancer Biology, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA;(5) Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA;(6) Department of Biological Sciences, College of Arts and Sciences, University of North Texas, 1155 Union Circle #305220, Denton, TX 76203, USA; |
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Abstract: | Metabolomics is the comprehensive profiling of the small molecule composition of a biological sample. Since metabolites are
often the indirect products of gene expression, this approach is being used to provide new insights into a variety of biological
systems (clinical, bioenergy, etc.). A grand challenge for metabolomics is the complexity of the data, which often include
many experimental artifacts. This is compounded by the tremendous chemical diversity of metabolites. Identification of each
uncharacterized metabolite is in many ways its own puzzle (compared with proteomics, which is based on predictable fragmentation
patterns of polypeptides). Therefore, effective data reduction/prioritization strategies are critical for this rapidly developing
field. Here we review liquid chromatography electrospray ionization mass spectrometry (LC/MS)-based metabolomics, methods
for feature finding/prioritization, approaches for identifying unknown metabolites, and construction of method specific ‘Metabolite
Atlases’. |
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