Transformer-based artificial neural networks for the conversion between chemical notations

We developed a Transformer-based artificial neural approach to translate between SMILES and IUPAC chemical notations: Struct2IUPAC and IUPAC2Struct. The overall performance level of our model is comparable to the rule-based solutions. We proved that the accuracy and speed of computations as well as...

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Detalles Bibliográficos
Autores principales: Krasnov, Lev, Khokhlov, Ivan, Fedorov, Maxim V., Sosnin, Sergey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292511/
https://www.ncbi.nlm.nih.gov/pubmed/34285269
http://dx.doi.org/10.1038/s41598-021-94082-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292511/
https://www.ncbi.nlm.nih.gov/pubmed/34285269
http://dx.doi.org/10.1038/s41598-021-94082-y

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