Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval

P Notin, M Dias, J Frazer… - International …, 2022 - proceedings.mlr.press
The ability to accurately model the fitness landscape of protein sequences is critical to a
wide range of applications, from quantifying the effects of human variants on disease …
被引用次数：144 相关文章

Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval

P Notin, M Dias, J Frazer, J Marchena-Hurtado… - arXiv e …, 2022 - ui.adsabs.harvard.edu
The ability to accurately model the fitness landscape of protein sequences is critical to a
wide range of applications, from quantifying the effects of human variants on disease …
[PDF] icml.cc

[PDF][PDF] Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval

P Notin, M Dias, J Frazer, J Marchena-Hurtado… - … Conference on Machine …, 2022 - icml.cc
1. Hopf et al. Mutation effects predicted from sequence co-variation. Nature Biotechnology,
2017 2. Riesselman, Ingraham et al. Deep generative models of genetic variation capture …

Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval

P Notin, M Dias, J Frazer, J Marchena-Hurtado… - arXiv preprint arXiv …, 2022 - arxiv.org
The ability to accurately model the fitness landscape of protein sequences is critical to a
wide range of applications, from quantifying the effects of human variants on disease …
[PDF] icml.cc

[PDF][PDF] Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval

P Notin, M Dias, J Frazer, J Marchena-Hurtado… - … Conference on Machine …, 2022 - icml.cc
1. Hopf et al. Mutation effects predicted from sequence co-variation. Nature Biotechnology,
2017 2. Riesselman, Ingraham et al. Deep generative models of genetic variation capture …