Julio R. Banga

The paper benchmarks optimization methods for parameter estimation in life sciences, identifying performance tiers and proposing a hybrid strategy that improves solution quality and robustness.

This paper introduces eLSHADE+, a metaheuristic for robust model calibration in systems biology, showing improved convergence and accuracy over existing methods.

The paper introduces a host-aware framework to identify transferable gene expression biopart parameters from combinatorial libraries, revealing intrinsic properties of transcriptional units.

This paper presents a methodology to improve dynamic microbial community models by addressing identifiability, stability, and overfitting issues through a comprehensive workflow.

This paper compares parallel global optimization solvers for parameter estimation in whole-brain epilepsy models, showing improved scalability and performance with Bayesian optimization and uncertainty quantification.

This paper develops a rule-based cell cycle model for RPE-1 cells that explains 16 observables and improves model reusability through PEtab specification.

The paper develops a method to automatically discover structurally identifiable and interpretable dynamical models from biological data using SINDy-PI and additional procedures.

This paper develops a method to evaluate energy yield and driving force in microbial metabolic pathways using thermodynamic principles and multi-objective optimization, applied to propionate oxidation and reverse TCA cycle.

This paper presents an optimization-based method to design synthetic gene circuits with specified bifurcation diagrams, focusing on mushroom bifurcation for applications in biosensors and synthetic biology.

OptDesign identifies optimal strain design strategies for biochemical production in E. coli by combining regulation and knockout interventions using a two-step approach.

This paper develops a multicriteria optimal control framework to predict enzyme activation and metabolite concentrations in complex metabolic pathways, demonstrating its application to yeast and Bacillus subtilis.

The paper benchmarks optimization methods for parameter estimation in large kinetic models and finds that a hybrid metaheuristic outperforms multi-start local searches.