Fig. 1 | Nature Communications

Fig. 1

From: Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models

Fig. 1

Machine learning of catalytic turnover numbers for genome-scale metabolic model (GEM) parameterization. A feature set from diverse classes is curated and mapped to independently build machine learning (ML) models of both kcat in vitro (f(x)) and kapp,max in vivo (g(x)). The inferred ML models are used to predict kcat in vitro or kapp,max at the genome-scale to parameterize GEMs

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