The new method predicts enzyme kinetic parameters using deep learning, reducing metabolic flux variability by several folds and improving model accuracy in growth rate and proteome fraction predictions.
#Ecgems #DeepLearning #KineticParameters
#Ecgems #DeepLearning #KineticParameters
Median flux variability reduced by several folds
Source: PLOS Computational Biology
realfeedapp.com
November 7, 2026 at 10:00 AM
The new method predicts enzyme kinetic parameters using deep learning, reducing metabolic flux variability by several folds and improving model accuracy in growth rate and proteome fraction predictions.
#Ecgems #DeepLearning #KineticParameters
#Ecgems #DeepLearning #KineticParameters
kinGEMs: A Robust and Scalable Framework forResource-Constraint Models through StochasticTuning of Deep Learning-Predicted KineticParameters https://www.biorxiv.org/content/10.64898/2026.03.14.711833v1
March 18, 2026 at 4:46 PM
kinGEMs: A Robust and Scalable Framework forResource-Constraint Models through StochasticTuning of Deep Learning-Predicted KineticParameters https://www.biorxiv.org/content/10.64898/2026.03.14.711833v1
kinGEMs: A Robust and Scalable Framework forResource-Constraint Models through StochasticTuning of Deep Learning-Predicted KineticParameters https://www.biorxiv.org/content/10.64898/2026.03.14.711833v1
March 18, 2026 at 4:46 PM
kinGEMs: A Robust and Scalable Framework forResource-Constraint Models through StochasticTuning of Deep Learning-Predicted KineticParameters https://www.biorxiv.org/content/10.64898/2026.03.14.711833v1