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Improved protein structure refinement guided by deep learning based accuracy estimation
We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutions to evaluate local atomic environments followed...
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| Pubblicato in: | Nat Commun |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7910447/ https://ncbi.nlm.nih.gov/pubmed/33637700 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-021-21511-x |
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