Efficient generative modeling of protein sequences using simple autoregressive models
Deep learning is a powerful tool for the design of novel protein sequences, yet can be computationally very inefficient. Here the authors propose using simple forecasting models to efficiently generate a large number of novel protein structures.
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| Main Authors: | , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/26264fe401544f27b9d9bdba0ab20a68 |
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