AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development
Jazyk angličtina Země Velká Británie, Anglie Médium print
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
733032
European Union's Horizon 2020 Research and Innovation Programme OBERON
PubMed
34718414
PubMed Central
PMC8796376
DOI
10.1093/bioinformatics/btab750
PII: 6414613
Knihovny.cz E-zdroje
- MeSH
- data management MeSH
- databáze faktografické MeSH
- dráhy škodlivých účinků * MeSH
- hodnocení rizik metody MeSH
- umělá inteligence MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
MOTIVATION: Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome. RESULTS: Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment. AVAILABILITY AND IMPLEMENTATION: AOP-helpFinder is available at http://aop-helpfinder.u-paris-sciences.fr/index.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
RECETOX Faculty of Science Masaryk University Brno CZ62500 Czech Republic
Université de Paris SPPIN CNRS UMR 8003 Paris F 75006 France
Université de Paris T3S Inserm UMR S1124 Paris F 75006 France
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Ankley G.T. et al. (2010) Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment. Environ. Toxicol. Chem., 29, 730–741. PubMed
Baker N. et al. (2017) Abstract Sifter: a comprehensive front-end system to PubMed. F1000Research, 6, 2164. PubMed PMC
Cañada A. et al. (2017) LimTox: a web tool for applied text mining of adverse event and toxicity associations of compounds, drugs and genes. Nucleic Acids Res., 45, W484–W489. PubMed PMC
Carvaillo J.-C. et al. (2019) Linking bisphenol S to adverse outcome pathways using a combined text mining and systems biology approach. Environ. Health Perspect., 127, 47005. PubMed PMC
Delrue N. et al. (2016) The adverse outcome pathway concept: a basis for developing regulatory decision-making tools. Altern. Lab. Anim., 44, 417–429. PubMed
Jornod F. et al. (2020) AOP4EUpest: mapping of pesticides in Adverse Outcome Pathways using a text mining tool. Bioinformatics, 36, 4379–4381. PubMed PMC
Parish S.T. et al. (2020) An evaluation framework for new approach methodologies (NAMs) for human health safety assessment. Regul. Toxicol. Pharmacol., 112, 104592. PubMed
Rugard M. et al. (2020) Deciphering adverse outcome pathway network linked to bisphenol F using text mining and systems toxicology approaches. Toxicol. Sci., 173, 32–40. PubMed PMC
Song J. et al. (2020) Upregulation of angiotensin converting enzyme 2 by shear stress reduced inflammation and proliferation in vascular endothelial cells. Biochem. Biophys. Res. Commun., 525, 812–818. PubMed
Williams A.J. et al. (2017) The CompTox chemistry dashboard: a community data resource for environmental chemistry. J. Cheminform., 9, 61. PubMed PMC
Zgheib E. et al. (2021) Identification of non-validated endocrine disrupting chemical characterization methods by screening of the literature using artificial intelligence and by database exploration. Environ. Int., 154, 106574. PubMed
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