| Campo DC | Valor | Idioma |
|---|
| dc.contributor.author | Veit-Acosta, Martina | - |
| dc.contributor.author | Walter Filgueira de Azevedo Junior | - |
| dc.date.accessioned | 2021-12-22T17:26:31Z | - |
| dc.date.available | 2021-12-22T17:26:31Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.issn | 0929-8673 | - |
| dc.identifier.uri | https://hdl.handle.net/10923/20664 | - |
| dc.language.iso | en | - |
| dc.relation.ispartof | CURRENT MEDICINAL CHEMISTRY | - |
| dc.rights | openAccess | - |
| dc.subject | protein-ligand interactions | - |
| dc.subject | Scoring Function Space | - |
| dc.subject | drug design | - |
| dc.subject | Machine learning | - |
| dc.subject | Crystallography | - |
| dc.subject | Deep Learning | - |
| dc.title | The Impact of CrystallographicData for the Development of Machine Learning Models to Predict Protein-Ligand Binding Affinity | - |
| dc.type | Article | - |
| dc.date.updated | 2021-12-22T17:26:29Z | - |
| dc.identifier.doi | DOI:10.2174/0929867328666210210121320 | - |
| dc.jtitle | CURRENT MEDICINAL CHEMISTRY | - |
| dc.volume | 28 | - |
| dc.spage | 1 | - |
| dc.epage | 15 | - |
| Aparece en las colecciones: | Artigo de Periódico
|
