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Open-source QSAR models for pKa prediction using multiple machine learning approaches.
Mansouri, Kamel; Cariello, Neal F; Korotcov, Alexandru; Tkachenko, Valery; Grulke, Chris M; Sprankle, Catherine S; Allen, David; Casey, Warren M; Kleinstreuer, Nicole C; Williams, Antony J.
Afiliación
  • Mansouri K; Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC, 27709, USA. kmansouri@ils-inc.com.
  • Cariello NF; Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
  • Korotcov A; Science Data Software LLC, 14914 Bradwill Court, Rockville, MD, 20850, USA.
  • Tkachenko V; Science Data Software LLC, 14914 Bradwill Court, Rockville, MD, 20850, USA.
  • Grulke CM; National Center for Computational Toxicology, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Mail Code D143-02, Research Triangle Park, NC, 27709, USA.
  • Sprankle CS; Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
  • Allen D; Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
  • Casey WM; National Institute of Environmental Health Sciences, P.O. Box 12233, Mail Stop K2-16, Research Triangle Park, NC, 27709, USA.
  • Kleinstreuer NC; National Institute of Environmental Health Sciences, P.O. Box 12233, Mail Stop K2-16, Research Triangle Park, NC, 27709, USA.
  • Williams AJ; National Center for Computational Toxicology, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Mail Code D143-02, Research Triangle Park, NC, 27709, USA.
J Cheminform ; 11(1): 60, 2019 Sep 18.
Article en En | MEDLINE | ID: mdl-33430972
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Cheminform Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Cheminform Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido