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...

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Detalles Bibliográficos
Autores principales: Ma, Eddie YT, Cameron, Christopher JF, Kremer, Stefan C
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Research
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

Internet

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

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