Modeling multiple experiments using regularized optimization: A case study on bacterial glucose utilization dynamics
A global model for glucose utilization is proposed based on time-varying parameters. Optimization with regularization allows identifying global models across experiments. Local and global parameters can be identified using particle swarm optimization. Results are validated by predicting new conditions and through model integration.
modeling regularization optimization particle swarm optimization identification biochemical systems bacterial metabolism