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: Pr...
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| Principais autores: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Taylor & Francis Group
2021-07-01
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| Series: | Future Science OA |
| Assuntos: | |
| Acceso en liña: | https://www.future-science.com/doi/10.2144/fsoa-2021-0033 |
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