Compound dataset and custom code for deep generative multi-target compound design

AIM: Generating a data and software infrastructure for evaluating multi-target compound (MT-CPD) design via deep generative modeling. METHODOLOGY: The REINVENT 2.0 approach for generative modeling was extended for MT-CPD design and a large benchmark data set was curated. EXEMPLARY RESULTS & DATA...

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Detalles Bibliográficos
Autores principales: Blaschke, Thomas, Bajorath, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Science Ltd 2021
Materias:
Data Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147756/
https://www.ncbi.nlm.nih.gov/pubmed/34046209
http://dx.doi.org/10.2144/fsoa-2021-0033

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147756/
https://www.ncbi.nlm.nih.gov/pubmed/34046209
http://dx.doi.org/10.2144/fsoa-2021-0033

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