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Classifying and scoring of molecules with the NGN: new datasets, significance tests, and generalization
This paper demonstrates how a Neural Grammar Network learns to classify and score molecules for a variety of tasks in chemistry and toxicology. In addition to a more detailed analysis on datasets previously studied, we introduce three new datasets (BBB, FXa, and toxicology) to show the generality of...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2010
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2966291/ https://www.ncbi.nlm.nih.gov/pubmed/21034429 http://dx.doi.org/10.1186/1471-2105-11-S8-S4 |