Estimation and validation of solubility of recombinant protein in E. coli strains via various advanced machine learning models

Abstract This study presents a comprehensive approach to predicting solubility of recombinant protein in four E. coli samples by employing machine learning techniques and optimization algorithms. Various models, including AdaBoost, Decision Tree Regression (DT), Gaussian Process Regression (GPR), an...

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Auteurs principaux:	Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah
Format:	Artigo
Langue:	Inglês
Publié:	Nature Portfolio 2025-04-01
Collection:	Scientific Reports
Sujets:	Recombinant protein Solubility Decision tree regression K-Nearest neighbors Gaussian process regression
Accès en ligne:	https://doi.org/10.1038/s41598-025-97445-x
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