| DLAB: deep learning methods for structure-based virtual screening of antibodies C Schneider, A Buchanan, B Taddese, CM Deane Bioinformatics 38 (2), 377-383, 2022 | 66 | 2022 |
| SAbDab in the age of biotherapeutics: updates including SAbDab-nano, the nanobody structure tracker C Schneider, MIJ Raybould, CM Deane Nucleic acids research 50 (D1), D1368-D1372, 2022 | 65 | 2022 |
| Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies SA Robinson, MIJ Raybould, C Schneider, WK Wong, C Marks, ... PLoS computational biology 17 (12), e1009675, 2021 | 33 | 2021 |
| Epitope profiling of coronavirus-binding antibodies using computational structural modelling SA Robinson, MIJ Raybould, C Schneider, WK Wong, C Marks, ... bioRxiv, 2021.04. 12.439478, 2021 | 8 | 2021 |
| Investigating the Volume and Diversity of Data Needed for Generalizable Antibody-Antigen ΔΔG Prediction AM Hummer, C Schneider, L Chinery, CM Deane bioRxiv, 2023.05. 17.541222, 2023 | 7 | 2023 |
| Inverse folding for antibody sequence design using deep learning FA Dreyer, D Cutting, C Schneider, H Kenlay, CM Deane arXiv preprint arXiv:2310.19513, 2023 | 3 | 2023 |
| Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking M Giulini, C Schneider, D Cutting, N Desai, C Deane, AMJJ Bonvin bioRxiv, 2023.11. 17.567543, 2023 | 2 | 2023 |
| Deep learning algorithms for predicting association between antibody sequence, structure, and antibody properties CC Schneider University of Oxford, 2021 | 2 | 2021 |
| De novo design of antibody heavy chains with SE (3) diffusion FA Dreyer, D Cutting, D Errington, C Schneider, C Deane NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development, 2023 | | 2023 |
| Epitope profiling of coronavirus-binding antibodies using computational structural modelling (preprint) SA Robinson, MIJ Raybould, C Marks, C Schneider, WK Wong, ... | | 2021 |
