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CPANNatNIC software for counter-propagation neural network to assist in read-across.
Drgan, Viktor; Zuperl, Spela; Vracko, Marjan; Cappelli, Claudia Ileana; Novic, Marjana.
Afiliación
  • Drgan V; Department of Cheminformatics, National Institute of Chemistry, Hajdrihova 19, 1001, Ljubljana, Slovenia. viktor.drgan@ki.si.
  • Zuperl S; Department of Cheminformatics, National Institute of Chemistry, Hajdrihova 19, 1001, Ljubljana, Slovenia.
  • Vracko M; Department of Cheminformatics, National Institute of Chemistry, Hajdrihova 19, 1001, Ljubljana, Slovenia.
  • Cappelli CI; Laboratory of Environmental Chemistry and Toxicology, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, Milan, Italy.
  • Novic M; Department of Cheminformatics, National Institute of Chemistry, Hajdrihova 19, 1001, Ljubljana, Slovenia.
J Cheminform ; 9(1): 30, 2017 May 22.
Article en En | MEDLINE | ID: mdl-29086050
BACKGROUND: CPANNatNIC is software for development of counter-propagation artificial neural network models. Besides the interface for training of a new neural network it also provides an interface for visualisation of the results which was developed to aid in interpretation of the results and to use the program as a tool for read-across. RESULTS: The work presents the details of the program's interface. Parts of the interface are presented and how they can be used. The examples provided show how the user can build a new model and view the results of predictions using the interface. Examples are given to show how the software may be used in read-across. CONCLUSIONS: CPANNatNIC provides a simple user interface for model development and visualisation. The interface implements options which may simplify read-across procedure. Statistical results show better prediction accuracy of read-across predictions than model predictions where similar compounds could be identified, which indicates the importance of using read-across and usefulness of the program.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Cheminform Año: 2017 Tipo del documento: Article País de afiliación: Eslovenia Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Cheminform Año: 2017 Tipo del documento: Article País de afiliación: Eslovenia Pais de publicación: Reino Unido