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2-D chemical structure image-based in silico model to predict agonist activity for androgen receptor
BACKGROUND: Abnormal activation of human nuclear hormone receptors disrupts endocrine systems and thereby affects human health. There have been machine learning-based models to predict androgen receptor agonist activity. However, the models were constructed based on limited numerical features such a...
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| Publicado no: | BMC Bioinformatics |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7586653/ https://ncbi.nlm.nih.gov/pubmed/33106158 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-020-03588-1 |
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