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The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites

The identification of unknown chemicals has emerged as a significant issue in untargeted metabolome analysis owing to the limited availability of purified standards for identification; this is a major bottleneck for the accumulation of reusable metabolome data in systems biology. Public resources fo...

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Autores principales: Sakurai, Nozomu, Yamazaki, Shinichi, Suda, Kunihiro, Hosoki, Ai, Akimoto, Nayumi, Takahashi, Haruya, Shibata, Daisuke, Aoki, Yuichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825447/
https://www.ncbi.nlm.nih.gov/pubmed/36417935
http://dx.doi.org/10.1093/nar/gkac1058
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author Sakurai, Nozomu
Yamazaki, Shinichi
Suda, Kunihiro
Hosoki, Ai
Akimoto, Nayumi
Takahashi, Haruya
Shibata, Daisuke
Aoki, Yuichi
author_facet Sakurai, Nozomu
Yamazaki, Shinichi
Suda, Kunihiro
Hosoki, Ai
Akimoto, Nayumi
Takahashi, Haruya
Shibata, Daisuke
Aoki, Yuichi
author_sort Sakurai, Nozomu
collection PubMed
description The identification of unknown chemicals has emerged as a significant issue in untargeted metabolome analysis owing to the limited availability of purified standards for identification; this is a major bottleneck for the accumulation of reusable metabolome data in systems biology. Public resources for discovering and prioritizing the unknowns that should be subject to practical identification, as well as further detailed study of spending costs and the risks of misprediction, are lacking. As such a resource, we released databases, Food-, Plant- and Thing-Metabolome Repository (http://metabolites.in/foods, http://metabolites.in/plants, and http://metabolites.in/things, referred to as XMRs) in which the sample-specific localization of unknowns detected by liquid chromatography–mass spectrometry in a wide variety of samples can be examined, helping to discover and prioritize the unknowns. A set of application programming interfaces for the XMRs facilitates the use of metabolome data for large-scale analysis and data mining. Several applications of XMRs, including integrated metabolome and genome analyses, are presented. Expanding the concept of XMRs will accelerate the identification of unknowns and increase the discovery of new knowledge.
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spelling pubmed-98254472023-01-10 The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites Sakurai, Nozomu Yamazaki, Shinichi Suda, Kunihiro Hosoki, Ai Akimoto, Nayumi Takahashi, Haruya Shibata, Daisuke Aoki, Yuichi Nucleic Acids Res Database Issue The identification of unknown chemicals has emerged as a significant issue in untargeted metabolome analysis owing to the limited availability of purified standards for identification; this is a major bottleneck for the accumulation of reusable metabolome data in systems biology. Public resources for discovering and prioritizing the unknowns that should be subject to practical identification, as well as further detailed study of spending costs and the risks of misprediction, are lacking. As such a resource, we released databases, Food-, Plant- and Thing-Metabolome Repository (http://metabolites.in/foods, http://metabolites.in/plants, and http://metabolites.in/things, referred to as XMRs) in which the sample-specific localization of unknowns detected by liquid chromatography–mass spectrometry in a wide variety of samples can be examined, helping to discover and prioritize the unknowns. A set of application programming interfaces for the XMRs facilitates the use of metabolome data for large-scale analysis and data mining. Several applications of XMRs, including integrated metabolome and genome analyses, are presented. Expanding the concept of XMRs will accelerate the identification of unknowns and increase the discovery of new knowledge. Oxford University Press 2022-11-24 /pmc/articles/PMC9825447/ /pubmed/36417935 http://dx.doi.org/10.1093/nar/gkac1058 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Sakurai, Nozomu
Yamazaki, Shinichi
Suda, Kunihiro
Hosoki, Ai
Akimoto, Nayumi
Takahashi, Haruya
Shibata, Daisuke
Aoki, Yuichi
The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites
title The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites
title_full The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites
title_fullStr The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites
title_full_unstemmed The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites
title_short The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites
title_sort thing metabolome repository family (xmrs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825447/
https://www.ncbi.nlm.nih.gov/pubmed/36417935
http://dx.doi.org/10.1093/nar/gkac1058
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