Inverse folding for antibody sequence design using deep learning
| Title: | Inverse folding for antibody sequence design using deep learning |
|---|---|
| Authors: | Frédéric A. Dreyer; Daniel Cutting; Constantin Schneider; Henry Kenlay; Charlotte M. Deane |
| Publisher Information: | Zenodo |
| Publication Year: | 2023 |
| Collection: | Zenodo |
| Description: | Model weights of the AbMPNN model (arXiv:2310.19513) presented at the 2023 ICML Workshop on Computational Biology, and csv files with the split between train, test and validation across the SAbDab and ImmuneBuilder datasets. This model is based on ProteinMPNN and can be run using the corresponding code: https://github.com/dauparas/ProteinMPNN. |
| Document Type: | dataset |
| Language: | unknown |
| Relation: | https://zenodo.org/records/8164693; oai:zenodo.org:8164693; https://doi.org/10.5281/zenodo.8164693 |
| DOI: | 10.5281/zenodo.8164693 |
| Availability: | https://doi.org/10.5281/zenodo.8164693; https://zenodo.org/records/8164693 |
| Rights: | Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode |
| Accession Number: | edsbas.C4636961 |
| Database: | BASE |