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Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes.
Agajanian, Steve; Odeyemi, Oluyemi; Bischoff, Nathaniel; Ratra, Simrath; Verkhivker, Gennady M.
Afiliação
  • Agajanian S; Graduate Program in Computational and Data Sciences, Department of Computational Sciences, Schmid College of Science and Technology , Chapman University , One University Drive, Orange , California 92866 , United States.
  • Odeyemi O; Graduate Program in Computational and Data Sciences, Department of Computational Sciences, Schmid College of Science and Technology , Chapman University , One University Drive, Orange , California 92866 , United States.
  • Bischoff N; Graduate Program in Computational and Data Sciences, Department of Computational Sciences, Schmid College of Science and Technology , Chapman University , One University Drive, Orange , California 92866 , United States.
  • Ratra S; Graduate Program in Computational and Data Sciences, Department of Computational Sciences, Schmid College of Science and Technology , Chapman University , One University Drive, Orange , California 92866 , United States.
  • Verkhivker GM; Graduate Program in Computational and Data Sciences, Department of Computational Sciences, Schmid College of Science and Technology , Chapman University , One University Drive, Orange , California 92866 , United States.
J Chem Inf Model ; 58(10): 2131-2150, 2018 10 22.
Article em En | MEDLINE | ID: mdl-30253099
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oncogenes / Genes Supressores de Tumor / Aprendizado de Máquina / Neoplasias Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Humans Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oncogenes / Genes Supressores de Tumor / Aprendizado de Máquina / Neoplasias Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Humans Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos