Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms.

Mukherjee, Rajib; Beykal, Burcu; Szafran, Adam T; Onel, Melis; Stossi, Fabio; Mancini, Maureen G; Lloyd, Dillon; Wright, Fred A; Zhou, Lan; Mancini, Michael A; Pistikopoulos, Efstratios N

Mukherjee, Rajib; Beykal, Burcu; Szafran, Adam T; Onel, Melis; Stossi, Fabio; Mancini, Maureen G; Lloyd, Dillon; Wright, Fred A; Zhou, Lan; Mancini, Michael A; Pistikopoulos, Efstratios N.

Afiliação

Mukherjee R; Texas A&M Energy Institute, Texas A&M University, College Station, TX, United States of America.
Beykal B; Texas A&M Energy Institute, Texas A&M University, College Station, TX, United States of America.
Szafran AT; Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United States of America.
Onel M; Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States of America.
Stossi F; Texas A&M Energy Institute, Texas A&M University, College Station, TX, United States of America.
Mancini MG; Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United States of America.
Lloyd D; Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States of America.
Wright FA; GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, United States of America.
Zhou L; Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States of America.
Mancini MA; GCC Center for Advanced Microscopy and Image Informatics, Houston, TX, United States of America.
Pistikopoulos EN; Bioinformatics Research Center, Center for Human Health and the Environment, Department of Statistics, North Carolina State University, Raleigh, NC, United States of America.

PLoS Comput Biol ; 16(9): e1008191, 2020 09.

Article em En | MEDLINE | ID: mdl-32970665

Assuntos

Algoritmos; Estrogênios/classificação; Aprendizado de Máquina; Linhagem Celular; Estrogênios/metabolismo; Humanos; Receptores de Estrogênio/metabolismo

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Estrogênios / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

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