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Charge and hydrophobicity are key features in sequence-trained machine learning models for predicting the biophysical properties of clinical-stage antibodies
Improved understanding of properties that mediate protein solubility and resistance to aggregation are important for developing biopharmaceuticals, and more generally in biotechnology and synthetic biology. Recent acquisition of large datasets for antibody biophysical properties enables the search f...
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| Опубликовано в: : | PeerJ |
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| Главные авторы: | , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
PeerJ Inc.
2019
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6967001/ https://ncbi.nlm.nih.gov/pubmed/31976163 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj.8199 |
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