NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data
Montemurro et al. present NetTCR-2.0, a convolutional neural network-based tool for predicting the interactions between T cell receptors and MHC-peptide complexes. This tool demonstrates that the best predictions are made when CDR3 α or CDR3 β binding data are used in combination.
Guardado en:
| Autores principales: | , , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/0fd24268ab1c4d9e95f4d96aaa1b710a |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | Montemurro et al. present NetTCR-2.0, a convolutional neural network-based tool for predicting the interactions between T cell receptors and MHC-peptide complexes. This tool demonstrates that the best predictions are made when CDR3 α or CDR3 β binding data are used in combination. |
|---|