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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Recombinant protein
Solubility
Decision tree regression
K-Nearest neighbors
Gaussian process regression
Online Access:https://doi.org/10.1038/s41598-025-97445-x
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-97445-x

Similar Items