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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...

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Detalles Bibliográficos
Autores principales: Heckmann, David, Lloyd, Colton J., Mih, Nathan, Ha, Yuanchi, Zielinski, Daniel C., Haiman, Zachary B., Desouki, Abdelmoneim Amer, Lercher, Martin J., Palsson, Bernhard O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
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