Exploring QSAR models for activity-cliff prediction.

Dablander, Markus; Hanser, Thierry; Lambiotte, Renaud; Morris, Garrett M

Dablander, Markus; Hanser, Thierry; Lambiotte, Renaud; Morris, Garrett M.

Afiliação

Dablander M; Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter (550), Woodstock Road, Oxford, OX2 6GG, UK.
Hanser T; Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK.
Lambiotte R; Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter (550), Woodstock Road, Oxford, OX2 6GG, UK.
Morris GM; Department of Statistics, University of Oxford, 24-29 St Giles', Oxford, OX1 3LB, UK. garrett.morris@stats.ox.ac.uk.

J Cheminform ; 15(1): 47, 2023 Apr 17.

Article em En | MEDLINE | ID: mdl-37069675

Palavras-chave

Activity cliff prediction; Activity cliffs; Binding affinity prediction; Deep learning; Extended-connectivity fingerprints; Graph isomorphism networks; Machine learning; Molecular representation; Physicochemical descriptors; QSAR modelling

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Cheminform Ano de publicação: 2023 Tipo de documento: Article

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