53 research outputs found

    Computational Characterisation of Chemicals and Datasets in Terms of Organic Functional Groups - a New Toxtree Rulebase

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    Toxtree is a freely available, user-friendly and extensible software application that is designed to make structure-based predictions for a number of toxicological endpoints and mechanisms of chemical action. The platform has been developed by the Joint Research Centre in collaboration with Ideaconsult Ltd (Sofia, Bulgaria) with a range of modules developed by various contributors. One of the modules developed as an extension to Toxtree is aimed at the identification of organic functional groups in query chemicals. The rulebase consists of 204 organic functional groups recognised by the “Checkmol” program, which was developed by Dr Norbert Haider, University of Vienna. A new Functional Group Profiler, has been coded as a Toxtree module by the Istituto Superiore di Sanita’ (Rome, Italy). The Toxtree profiler, called ISSFUNC, can be used to screen and characterise chemicals as a basis for read-across, category formation and (Q)SAR analysis. It can also be used for the global comparison of datasets, such as model training and test sets and chemical inventories.JRC.DG.I.6-Systems toxicolog

    Development of Structural Alerts for the In Vivo Micronucleus Assay in Rodents

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    In vivo mutagenicity and carcinogenicity studies are posing a high demand for test-related resources. Among these studies, the micronucleus test in rodents is the most widely used, as follow up to positive in vitro mutagenicity results. A recent survey of the (Q)SAR models for mutagenicity and carcinogenicity has indicated that no (Q)SAR models for in vivo micronucleus are available in the public domain. Therefore, the development and extensive use of estimation techniques such as (Q)SARs, read-across and grouping of chemicals, promises to have a huge animal saving potential for this endpoint. In this report, we describe the identification of structural alerts for the in vivo micronucleus assay, and provide the list of underlying chemical structures. These structural alerts provide a coarse-grain filter for the preliminary screening of potential in vivo mutagens.JRC.I.6-Systems toxicolog

    OpenTox predictive toxicology framework: toxicological ontology and semantic media wiki-based OpenToxipedia

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    <p>Abstract</p> <p>Background</p> <p>The OpenTox Framework, developed by the partners in the OpenTox project (<url>http://www.opentox.org</url>), aims at providing a unified access to toxicity data, predictive models and validation procedures. Interoperability of resources is achieved using a common information model, based on the OpenTox ontologies, describing predictive algorithms, models and toxicity data. As toxicological data may come from different, heterogeneous sources, a deployed ontology, unifying the terminology and the resources, is critical for the rational and reliable organization of the data, and its automatic processing.</p> <p>Results</p> <p>The following related ontologies have been developed for OpenTox: a) Toxicological ontology – listing the toxicological endpoints; b) Organs system and Effects ontology – addressing organs, targets/examinations and effects observed in <it>in vivo</it> studies; c) ToxML ontology – representing semi-automatic conversion of the ToxML schema; d) OpenTox ontology– representation of OpenTox framework components: chemical compounds, datasets, types of algorithms, models and validation web services; e) ToxLink–ToxCast assays ontology and f) OpenToxipedia community knowledge resource on toxicology terminology.</p> <p>OpenTox components are made available through standardized REST web services, where every compound, data set, and predictive method has a unique resolvable address (URI), used to retrieve its Resource Description Framework (RDF) representation, or to initiate the associated calculations and generate new RDF-based resources.</p> <p>The services support the integration of toxicity and chemical data from various sources, the generation and validation of computer models for toxic effects, seamless integration of new algorithms and scientifically sound validation routines and provide a flexible framework, which allows building arbitrary number of applications, tailored to solving different problems by end users (e.g. toxicologists).</p> <p>Availability</p> <p>The OpenTox toxicological ontology projects may be accessed via the OpenTox ontology development page <url>http://www.opentox.org/dev/ontology</url>; the OpenTox ontology is available as OWL at <url>http://opentox.org/api/1 1/opentox.owl</url>, the ToxML - OWL conversion utility is an open source resource available at <url>http://ambit.svn.sourceforge.net/viewvc/ambit/branches/toxml-utils/</url></p

    Collaborative development of predictive toxicology applications

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    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
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