New yeast model can improve protein production NatureComms
Machine learning was integrated to score the importance of factors. In this study, various factors were used as the input features and the maximum recombinant protein production rate was used as the target label. We split the created dataset into a training dataset and testing dataset at the ratio of 80% and 20%, respectively. A random forest regressor with 10 estimators was used to train the model.
. Python with SHAP , scikit-learn , pandas , SciPy , NumPy and Matplotlib were used in the analysis and visualization. Five-fold cross validation was performed.Identification of overexpression targets for improving recombinant protein production was performed using the concept of FSEOFbut to identify the proteins with increased expression during the enforcement of recombinant protein production.
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