eprintid: 1478 rev_number: 9 eprint_status: archive userid: 44 dir: disk0/00/00/14/78 datestamp: 2013-02-14 08:56:34 lastmod: 2013-09-12 12:16:45 status_changed: 2013-02-14 08:56:34 type: article metadata_visibility: show creators_name: Hardy, Barry creators_name: Douglas, Nicki creators_name: Helma, Christoph creators_name: Rautenberg, Micha creators_name: Jeliazkova, Nina creators_name: Jeliazkov, Vedrin creators_name: Nikolova, Ivelina creators_name: Benigni, Romualdo creators_name: Tcheremenskaia, Olga creators_name: Kramer, Stefan creators_name: Girschick, Tobias creators_name: Buchwald, Fabian creators_name: Wicker, Joerg creators_name: Karwath, Andreas creators_name: Gutlein, Martin creators_name: Maunz, Andreas creators_name: Sarimveis, Haralambos creators_name: Melagraki, Georgia creators_name: Afantitis, Antreas creators_name: Sopasakis, Pantelis creators_name: Gallagher, David creators_name: Poroikov, Vladimir creators_name: Filimonov, Dmitry creators_name: Zakharov, Alexey creators_name: Lagunin, Alexey creators_name: Gloriozova, Tatyana creators_name: Novikov, Sergey creators_name: Skvortsova, Natalia creators_name: Druzhilovsky, Dmitry creators_name: Chawla, Sunil creators_name: Ghosh, Indira creators_name: Ray, Surajit creators_name: Patel, Hitesh creators_name: Escher, Sylvia creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: pantelis.sopasakis@imtlucca.it creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: title: Collaborative development of predictive toxicology applications ispublished: pub subjects: QA76 divisions: CSA full_text_status: public abstract: OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals. The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation. Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way. date: 2010 date_type: published publication: Journal of Cheminformatics volume: 2 number: 1 publisher: Chemistry Central pagerange: 7 id_number: 10.1186/1758-2946-2-7 refereed: TRUE issn: 1758-2946 official_url: http://dx.doi.org/10.1186/1758-2946-2-7 citation: Hardy, Barry and Douglas, Nicki and Helma, Christoph and Rautenberg, Micha and Jeliazkova, Nina and Jeliazkov, Vedrin and Nikolova, Ivelina and Benigni, Romualdo and Tcheremenskaia, Olga and Kramer, Stefan and Girschick, Tobias and Buchwald, Fabian and Wicker, Joerg and Karwath, Andreas and Gutlein, Martin and Maunz, Andreas and Sarimveis, Haralambos and Melagraki, Georgia and Afantitis, Antreas and Sopasakis, Pantelis and Gallagher, David and Poroikov, Vladimir and Filimonov, Dmitry and Zakharov, Alexey and Lagunin, Alexey and Gloriozova, Tatyana and Novikov, Sergey and Skvortsova, Natalia and Druzhilovsky, Dmitry and Chawla, Sunil and Ghosh, Indira and Ray, Surajit and Patel, Hitesh and Escher, Sylvia Collaborative development of predictive toxicology applications. Journal of Cheminformatics, 2 (1). p. 7. ISSN 1758-2946 (2010) document_url: http://eprints.imtlucca.it/1478/1/Journal_of_Cheminformatics_2010_Sopasakis.pdf