Modern molecular discovery processes generate millions of measurements at different quality levels. Here, the authors develop a new deep learning method for transfer learning from low-cost and abundant data to enhance the efficiency of drug discovery.
Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting / Buterez, D.; Janet, J. P.; Kiddle, S. J.; Oglic, D.; Lio, P.. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 15:1(2024). [10.1038/s41467-024-45566-8]
Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting
Lio P.
2024
Abstract
Modern molecular discovery processes generate millions of measurements at different quality levels. Here, the authors develop a new deep learning method for transfer learning from low-cost and abundant data to enhance the efficiency of drug discovery.File allegati a questo prodotto
| File | Dimensione | Formato | |
|---|---|---|---|
|
Buterez_Transfer_2024.pdf
accesso aperto
Note: https://www.nature.com/articles/s41467-024-45566-8.pdf
Tipologia:
Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza:
Creative commons
Dimensione
2.27 MB
Formato
Adobe PDF
|
2.27 MB | Adobe PDF |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
