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ShinyTPs: Curating Transformation Products from Text Mining Results

[Image: see text] Transformation product (TP) information is essential to accurately evaluate the hazards compounds pose to human health and the environment. However, information about TPs is often limited, and existing data is often not fully Findable, Accessible, Interoperable, and Reusable (FAIR)...

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Autores principales: Palm, Emma H., Chirsir, Parviel, Krier, Jessy, Thiessen, Paul A., Zhang, Jian, Bolton, Evan E., Schymanski, Emma L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569035/
https://www.ncbi.nlm.nih.gov/pubmed/37840815
http://dx.doi.org/10.1021/acs.estlett.3c00537
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author Palm, Emma H.
Chirsir, Parviel
Krier, Jessy
Thiessen, Paul A.
Zhang, Jian
Bolton, Evan E.
Schymanski, Emma L.
author_facet Palm, Emma H.
Chirsir, Parviel
Krier, Jessy
Thiessen, Paul A.
Zhang, Jian
Bolton, Evan E.
Schymanski, Emma L.
author_sort Palm, Emma H.
collection PubMed
description [Image: see text] Transformation product (TP) information is essential to accurately evaluate the hazards compounds pose to human health and the environment. However, information about TPs is often limited, and existing data is often not fully Findable, Accessible, Interoperable, and Reusable (FAIR). FAIRifying existing TP knowledge is a relatively easy path toward improving access to data for identification workflows and for machine-learning-based algorithms. ShinyTPs was developed to curate existing transformation information derived from text-mined data within the PubChem database. The application (available as an R package) visualizes the text-mined chemical names to facilitate the user validation of the automatically extracted reactions. ShinyTPs was applied to a case study using 436 tentatively identified compounds to prioritize TP retrieval. This resulted in the extraction of 645 reactions (associated with 496 compounds), of which 319 were not previously available in PubChem. The curated reactions were added to the PubChem Transformations library, which was used as a TP suspect list for identification of TPs using the open-source workflow patRoon. In total, 72 compounds from the library were tentatively identified, 18% of which were curated using ShinyTPs, showing that the app can help support TP identification in non-target analysis workflows.
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spelling pubmed-105690352023-10-13 ShinyTPs: Curating Transformation Products from Text Mining Results Palm, Emma H. Chirsir, Parviel Krier, Jessy Thiessen, Paul A. Zhang, Jian Bolton, Evan E. Schymanski, Emma L. Environ Sci Technol Lett [Image: see text] Transformation product (TP) information is essential to accurately evaluate the hazards compounds pose to human health and the environment. However, information about TPs is often limited, and existing data is often not fully Findable, Accessible, Interoperable, and Reusable (FAIR). FAIRifying existing TP knowledge is a relatively easy path toward improving access to data for identification workflows and for machine-learning-based algorithms. ShinyTPs was developed to curate existing transformation information derived from text-mined data within the PubChem database. The application (available as an R package) visualizes the text-mined chemical names to facilitate the user validation of the automatically extracted reactions. ShinyTPs was applied to a case study using 436 tentatively identified compounds to prioritize TP retrieval. This resulted in the extraction of 645 reactions (associated with 496 compounds), of which 319 were not previously available in PubChem. The curated reactions were added to the PubChem Transformations library, which was used as a TP suspect list for identification of TPs using the open-source workflow patRoon. In total, 72 compounds from the library were tentatively identified, 18% of which were curated using ShinyTPs, showing that the app can help support TP identification in non-target analysis workflows. American Chemical Society 2023-09-29 /pmc/articles/PMC10569035/ /pubmed/37840815 http://dx.doi.org/10.1021/acs.estlett.3c00537 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Palm, Emma H.
Chirsir, Parviel
Krier, Jessy
Thiessen, Paul A.
Zhang, Jian
Bolton, Evan E.
Schymanski, Emma L.
ShinyTPs: Curating Transformation Products from Text Mining Results
title ShinyTPs: Curating Transformation Products from Text Mining Results
title_full ShinyTPs: Curating Transformation Products from Text Mining Results
title_fullStr ShinyTPs: Curating Transformation Products from Text Mining Results
title_full_unstemmed ShinyTPs: Curating Transformation Products from Text Mining Results
title_short ShinyTPs: Curating Transformation Products from Text Mining Results
title_sort shinytps: curating transformation products from text mining results
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569035/
https://www.ncbi.nlm.nih.gov/pubmed/37840815
http://dx.doi.org/10.1021/acs.estlett.3c00537
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