AI for predicting chemical-effect associations at the chemical universe level-deepFPlearn.

Schor, Jana; Scheibe, Patrick; Bernt, Matthias; Busch, Wibke; Lai, Chih; Hackermüller, Jörg

Schor, Jana; Scheibe, Patrick; Bernt, Matthias; Busch, Wibke; Lai, Chih; Hackermüller, Jörg.

Afiliação

Schor J; Department Computational Biology, Helmholtz Centre for environmental research - UFZ, Permoserstr. 15, 04318 Leipzig, Saxony, Germany.
Scheibe P; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Saxony, Germany.
Bernt M; Department Computational Biology, Helmholtz Centre for environmental research - UFZ, Permoserstr. 15, 04318 Leipzig, Saxony, Germany.
Busch W; Department of Bioanalytical Ecotoxicology, Helmholtz Centre for environmental research - UFZ, Permoserstr. 15, 04318 Leipzig, Saxony, Germany.
Lai C; Graduate Program in Software & School of Engineering, University of St. Thomas, 2115 Summit Ave, St. Paul, MN 55105, Minnesota, USA.
Hackermüller J; Department Computational Biology, Helmholtz Centre for environmental research - UFZ, Permoserstr. 15, 04318 Leipzig, Saxony, Germany.

Brief Bioinform ; 23(5)2022 09 20.

Article em En | MEDLINE | ID: mdl-35849097

Assuntos

Compressão de Dados; Redes Neurais de Computação; Medição de Risco

Palavras-chave

Deep learning; autoencoder; binary fingerprint; molecular structures; toxicology

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Compressão de Dados Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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