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DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach.
Khemchandani, Yash; O'Hagan, Stephen; Samanta, Soumitra; Swainston, Neil; Roberts, Timothy J; Bollegala, Danushka; Kell, Douglas B.
  • Khemchandani Y; Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Crown St, Liverpool, L69 7ZB, UK.
  • O'Hagan S; Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra, 400 076, India.
  • Samanta S; Dept of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess St, Manchester, M1 7DN, UK.
  • Swainston N; Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Crown St, Liverpool, L69 7ZB, UK.
  • Roberts TJ; Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Crown St, Liverpool, L69 7ZB, UK.
  • Bollegala D; Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Crown St, Liverpool, L69 7ZB, UK.
  • Kell DB; Dept of Computer Science, University of Liverpool, Ashton Building, Ashton Street, Liverpool, L69 3BX, UK.
J Cheminform ; 12(1): 53, 2020 Sep 04.
Article en En | MEDLINE | ID: mdl-33431037
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2020 Tipo del documento: Article
Texto completo
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XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2020 Tipo del documento: Article