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Deciphering protein evolution and fitness landscapes with latent space models
Protein sequences contain rich information about protein evolution, fitness landscapes, and stability. Here we investigate how latent space models trained using variational auto-encoders can infer these properties from sequences. Using both simulated and real sequences, we show that the low dimensio...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904478/ https://www.ncbi.nlm.nih.gov/pubmed/31822668 http://dx.doi.org/10.1038/s41467-019-13633-0 |