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Development of Predictive Models for Identifying Potential S100A9 Inhibitors Based on Machine Learning Methods
S100A9 is a potential therapeutic target for various disease including prostate cancer, colorectal cancer, and Alzheimer's disease. However, the sparsity of atomic level data, such as protein-protein interaction of S100A9 with RAGE, TLR4/MD2, or CD147 (EMMPRIN) hinders the rational drug design...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886474/ https://www.ncbi.nlm.nih.gov/pubmed/31824919 http://dx.doi.org/10.3389/fchem.2019.00779 |