AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development

Abstract 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...

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Veröffentlicht in:Bioinformatics 2022-01, Vol.38 (4), p.1173-1175
Hauptverfasser: Jornod, Florence, Jaylet, Thomas, Blaha, Ludek, Sarigiannis, Denis, Tamisier, Luc, Audouze, Karine
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container_end_page 1175
container_issue 4
container_start_page 1173
container_title Bioinformatics
container_volume 38
creator Jornod, Florence
Jaylet, Thomas
Blaha, Ludek
Sarigiannis, Denis
Tamisier, Luc
Audouze, Karine
description Abstract 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.
doi_str_mv 10.1093/bioinformatics/btab750
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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. 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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. 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source Oxford Journals Open Access Collection; MEDLINE; EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection
subjects Adverse Outcome Pathways
Applications Notes
Artificial Intelligence
Bioinformatics
Computer Science
Data Management
Databases, Factual
Life Sciences
Risk Assessment - methods
Toxicology
title AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development
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