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Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models
Knowing the catalytic turnover numbers of enzymes is essential for understanding the growth rate, proteome composition, and physiology of organisms, but experimental data on enzyme turnover numbers is sparse and noisy. Here, we demonstrate that machine learning can successfully predict catalytic tur...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6286351/ https://www.ncbi.nlm.nih.gov/pubmed/30531987 http://dx.doi.org/10.1038/s41467-018-07652-6 |