Reference : Empowering large chemical knowledge bases for exposomics: PubChemLite meets MetFrag
Scientific journals : Article
Life sciences : Environmental sciences & ecology
Systems Biomedicine
http://hdl.handle.net/10993/46907
Empowering large chemical knowledge bases for exposomics: PubChemLite meets MetFrag
English
Schymanski, Emma mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Kondic, Todor mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics]
Neumann, Steffen [> >]
Thiessen, Paul A. [> >]
Zhang, Jian [> >]
Bolton, Evan E. [> >]
Mar-2021
Journal of Cheminformatics
13
1
19
Yes (verified by ORBilu)
International
1758-2946
[en] Abstract Compound (or chemical) databases are an invaluable resource for many scientific disciplines. Exposomics researchers need to find and identify relevant chemicals that cover the entirety of potential (chemical and other) exposures over entire lifetimes. This daunting task, with over 100 million chemicals in the largest chemical databases, coupled with broadly acknowledged knowledge gaps in these resources, leaves researchers faced with too much—yet not enough—information at the same time to perform comprehensive exposomics research. Furthermore, the improvements in analytical technologies and computational mass spectrometry workflows coupled with the rapid growth in databases and increasing demand for high throughput “big data” services from the research community present significant challenges for both data hosts and workflow developers. This article explores how to reduce candidate search spaces in non-target small molecule identification workflows, while increasing content usability in the context of environmental and exposomics analyses, so as to profit from the increasing size and information content of large compound databases, while increasing efficiency at the same time. In this article, these methods are explored using PubChem, the NORMAN Network Suspect List Exchange and the in silico fragmentation approach MetFrag. A subset of the PubChem database relevant for exposomics, PubChemLite, is presented as a database resource that can be (and has been) integrated into current workflows for high resolution mass spectrometry. Benchmarking datasets from earlier publications are used to show how experimental knowledge and existing datasets can be used to detect and fill gaps in compound databases to progressively improve large resources such as PubChem, and topic-specific subsets such as PubChemLite. PubChemLite is a living collection, updating as annotation content in PubChem is updated, and exported to allow direct integration into existing workflows such as MetFrag. The source code and files necessary to recreate or adjust this are jointly hosted between the research parties (see data availability statement). This effort shows that enhancing the FAIRness (Findability, Accessibility, Interoperability and Reusability) of open resources can mutually enhance several resources for whole community benefit. The authors explicitly welcome additional community input on ideas for future developments.
Fonds National de la Recherche - FnR
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/46907
10.1186/s13321-021-00489-0
https://jcheminf.biomedcentral.com/articles/10.1186/s13321-021-00489-0
FnR ; FNR12341006 > Emma Schymanski > ECHIDNA > Environmental Cheminformatics To Identify Unknown Chemicals And Their Effects > 01/10/2018 > 30/09/2023 > 2018

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