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Predicting changes in protein thermodynamic stability upon point mutation with deep 3D convolutional neural networks
Predicting mutation-induced changes in protein thermodynamic stability (ΔΔG) is of great interest in protein engineering, variant interpretation, and protein biophysics. We introduce ThermoNet, a deep, 3D-convolutional neural network (3D-CNN) designed for structure-based prediction of ΔΔGs upon poin...
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| Gepubliceerd in: | PLoS Comput Biol |
|---|---|
| Hoofdauteurs: | , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Public Library of Science
2020
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7728386/ https://ncbi.nlm.nih.gov/pubmed/33253214 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1008291 |
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