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See detailEmpowering large chemical knowledge bases for exposomics: PubChemLite meets MetFrag
Schymanski, Emma UL; Kondic, Todor UL; Neumann, Steffen et al

in Journal of Cheminformatics (2021), 13(1), 19

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 ... [more ▼]

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. [less ▲]

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See detailEmpowering Large Chemical Knowledge Bases for Exposomics: PubChemLite Meets MetFrag
Schymanski, Emma UL; Kondic, Todor UL; Neumann, Steffen et al

E-print/Working paper (2020)

Detailed reference viewed: 78 (0 UL)
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See detailVirtual Podium Keynote: Compound Identification and Exposomics: DIY Databases?
Schymanski, Emma UL; Bolton, Evan; Helmus, Rick et al

Presentation (2020, April 10)

In light of recent events, many of us have been impacted by the cancellation of conferences and meetings. We are not only losing the opportunity to present our research, but a chance to connect with our ... [more ▼]

In light of recent events, many of us have been impacted by the cancellation of conferences and meetings. We are not only losing the opportunity to present our research, but a chance to connect with our community. Virtual Podium is a platform and opportunity to present and learn about compelling scientific research. Our third session will be focused on Compound Identification. Our keynote speaker this week will be Emma Schymanski who is the PI of Environmental Cheminformatics at the University of Luxembourg. Session 3: Compound Identification Friday, April 10, 2020 at 12:00-1:00PM PDT (3:00-4:00PM EDT) Session 3 - Compound Identification: https://www.eventbrite.com/e/101426613732 [less ▲]

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See detailPubChemLite for Exposomics
Bolton, Evan; Schymanski, Emma UL; Kondic, Todor UL et al

Computer development (2020)

Detailed reference viewed: 51 (2 UL)