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Machine Learning Models for Estrogen Receptor Bioactivity and Endocrine Disruption Prediction.
Zorn, Kimberley M; Foil, Daniel H; Lane, Thomas R; Russo, Daniel P; Hillwalker, Wendy; Feifarek, David J; Jones, Frank; Klaren, William D; Brinkman, Ashley M; Ekins, Sean.
Affiliation
  • Zorn KM; Collaborations Pharmaceuticals Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States.
  • Foil DH; Collaborations Pharmaceuticals Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States.
  • Lane TR; Collaborations Pharmaceuticals Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States.
  • Russo DP; Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey 08102, United States.
  • Hillwalker W; Global Product Safety, SC Johnson and Son, Inc., Racine, Wisconsin 53404, United States.
  • Feifarek DJ; Global Product Safety, SC Johnson and Son, Inc., Racine, Wisconsin 53404, United States.
  • Jones F; Global Product Safety, SC Johnson and Son, Inc., Racine, Wisconsin 53404, United States.
  • Klaren WD; Global Product Safety, SC Johnson and Son, Inc., Racine, Wisconsin 53404, United States.
  • Brinkman AM; Global Product Safety, SC Johnson and Son, Inc., Racine, Wisconsin 53404, United States.
  • Ekins S; Collaborations Pharmaceuticals Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States.
Environ Sci Technol ; 54(19): 12202-12213, 2020 10 06.
Article in En | MEDLINE | ID: mdl-32857505
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Full text: 1 Collection: 01-internacional Health context: 2_ODS3 Database: MEDLINE Main subject: Receptors, Estrogen / Endocrine Disruptors Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Environ Sci Technol Year: 2020 Document type: Article
Fulltext
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PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Health context: 2_ODS3 Database: MEDLINE Main subject: Receptors, Estrogen / Endocrine Disruptors Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Environ Sci Technol Year: 2020 Document type: Article