BioengineeringbioRxivPreprint
kinGEMs: A Robust and Scalable Framework for Resource-Constraint Models through Stochastic Tuning of Deep Learning-Predicted Kinetic Parameters
Rana Ahmed Barghout, Lya Chinas, Benjamín Sánchez-Lengeling, Radhakrishnan Mahadevan
This paper introduces kinGEMs, a framework that integrates deep learning-predicted kinetic parameters into genome-scale models to improve metabolic modeling accuracy and scalability.
DOI 10.64898/2026.03.14.711833