Flexible and transparent computational workflows for the prediction of target organ toxicity

Lade...
Vorschaubild
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2013
Autor:innen
Richarz, Andrea-Nicole
Enoch, Steven J.
Hewitt, Mark
Madden, Judith C.
Przybylak, Katarzyna
Yang, Chihae
Cronin, Mark T. D.
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Zusammenfassung

In silico modeling of target organ toxicity has been held back in part by an inability to capture all relevant information into a meaningful reductionist approach. It has also been considered at times too simplistic, using data of often variable quality and seldom allowing the user to assess the relevance to the intended use. The purpose of this study was to develop a novel computational toxicology workflow system, to allow the users greater control and understanding of the target organ toxicity prediction. The workflows were built on the KNIME open-access platform which allows pipelining via a graphical user interface. Various building blocks, known as nodes, were incorporated, to access chemical inventories and/or databases, to profile structures and calculate properties and to report prediction results. The “basic” user sees a web-interface, whilst a “trained” user can go behind this to interrogate the nodes and, if required, link to additional data sources or investigate and update the models. The workflow was developed to address in particular the prediction of target organ toxicity of cosmetic ingredients. It comprises an inventory of over 4,400 unique chemical structures (cosmetic ingredients and related substances). The database contains repeat dose toxicity data for over 1,100 compounds including NOEL values. Thus, a user is able to search for similar compounds in the inventory file or database. The compound is then profiled using relevant structural alerts and chemotypes, currently comprising 108 alerts for protein reactivity, 85 for DNA binding, 32 for phospholipidosis and 16 for other liver toxicity endpoints. The workflows are flexible and transparent, they are successful in guiding a user through the process of making a prediction of target organ toxicity. Supported by the EU FP7 COSMOS Project.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690RICHARZ, Andrea-Nicole, Steven J. ENOCH, Mark HEWITT, Judith C. MADDEN, Katarzyna PRZYBYLAK, Chihae YANG, Michael R. BERTHOLD, Thorsten MEINL, Peter OHL, Mark T. D. CRONIN, 2013. Flexible and transparent computational workflows for the prediction of target organ toxicity. In: The Toxicologist : Supplement to Toxicological Sciences. 2013, 132(1), pp. 183. ISSN 1096-6080
BibTex
@article{Richarz2013Flexi-37494,
  year={2013},
  title={Flexible and transparent computational workflows for the prediction of target organ toxicity},
  url={https://www.toxicology.org/pubs/docs/Tox/2013Tox.pdf},
  number={1},
  volume={132},
  issn={1096-6080},
  journal={The Toxicologist : Supplement to Toxicological Sciences},
  author={Richarz, Andrea-Nicole and Enoch, Steven J. and Hewitt, Mark and Madden, Judith C. and Przybylak, Katarzyna and Yang, Chihae and Berthold, Michael R. and Meinl, Thorsten and Ohl, Peter and Cronin, Mark T. D.}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/37494">
    <dc:contributor>Yang, Chihae</dc:contributor>
    <dc:contributor>Berthold, Michael R.</dc:contributor>
    <dc:creator>Przybylak, Katarzyna</dc:creator>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/37494"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:creator>Madden, Judith C.</dc:creator>
    <dc:creator>Enoch, Steven J.</dc:creator>
    <dc:language>eng</dc:language>
    <dc:creator>Ohl, Peter</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Hewitt, Mark</dc:creator>
    <dc:contributor>Ohl, Peter</dc:contributor>
    <dcterms:issued>2013</dcterms:issued>
    <dc:creator>Meinl, Thorsten</dc:creator>
    <dc:contributor>Enoch, Steven J.</dc:contributor>
    <dcterms:title>Flexible and transparent computational workflows for the prediction of target organ toxicity</dcterms:title>
    <dc:creator>Berthold, Michael R.</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Yang, Chihae</dc:creator>
    <dc:contributor>Cronin, Mark T. D.</dc:contributor>
    <dc:creator>Richarz, Andrea-Nicole</dc:creator>
    <dc:contributor>Hewitt, Mark</dc:contributor>
    <dc:contributor>Meinl, Thorsten</dc:contributor>
    <dc:creator>Cronin, Mark T. D.</dc:creator>
    <dc:contributor>Przybylak, Katarzyna</dc:contributor>
    <dcterms:abstract>In silico modeling of target organ toxicity has been held back in part by an inability to capture all relevant information into a meaningful reductionist approach. It has also been considered at times too simplistic, using data of often variable quality and seldom allowing the user to assess the relevance to the intended use. The purpose of this study was to develop a novel computational toxicology workflow system, to allow the users greater control and understanding of the target organ toxicity prediction. The workflows were built on the KNIME open-access platform which allows pipelining via a graphical user interface. Various building blocks, known as nodes, were incorporated, to access chemical inventories and/or databases, to profile structures and calculate properties and to report prediction results. The “basic” user sees a web-interface, whilst a “trained” user can go behind this to interrogate the nodes and, if required, link to additional data sources or investigate and update the models. The workflow was developed to address in particular the prediction of target organ toxicity of cosmetic ingredients. It comprises an inventory of over 4,400 unique chemical structures (cosmetic ingredients and related substances). The database contains repeat dose toxicity data for over 1,100 compounds including NOEL values. Thus, a user is able to search for similar compounds in the inventory file or database. The compound is then profiled using relevant structural alerts and chemotypes, currently comprising 108 alerts for protein reactivity, 85 for DNA binding, 32 for phospholipidosis and 16 for other liver toxicity endpoints. The workflows are flexible and transparent, they are successful in guiding a user through the process of making a prediction of target organ toxicity. Supported by the EU FP7 COSMOS Project.</dcterms:abstract>
    <dc:contributor>Richarz, Andrea-Nicole</dc:contributor>
    <dc:contributor>Madden, Judith C.</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-02-16T09:51:32Z</dcterms:available>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-02-16T09:51:32Z</dc:date>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
Prüfdatum der URL
2017-02-16
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Diese Publikation teilen