Julio R. Banga

Research Professor

Consejo Superior de Investigaciones Cientificas

Spain

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Julio R. Banga is a Research Professor at the Consejo Superior de Investigaciones Científicas in Spain. His research focuses on mechanistic dynamic modeling of biological systems, uncertainty quantification in dynamic biological systems, and the optimization of biological networks. Recent publications include advancements in synthetic gene circuit design and parameter estimation methods for computational models in epilepsy.

Articles (19)

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2025

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2022

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2022

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2022

Collaborators (6)

Natalio Krasnogor

Prof. at Newcastle University

Newcastle University

UNITED KINGDOM

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Manuel Pájaro Diéguez

Assistant Professor

Universidade de Vigo - Campus Ourense

SPAIN

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Bela Novak

University of Oxford

UNITED KINGDOM

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Alejandro F. Villaverde

Universidade de Vigo

SPAIN

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Shouyong Jiang

Lecturer in Machine Learning

University of Lincoln

UNITED KINGDOM

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Patricia González

Associate Professor

Universidade da Coruña

SPAIN

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Julio R. Banga

Research Interests

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About

Articles (19)

Mechanistic dynamic modelling of biological systems: The road ahead

Conformal prediction for uncertainty quantification in dynamic biological systems

Parameter estimation in a whole-brain network model of epilepsy: Comparison of parallel global optimization solvers

Population based metaheuristics in Spark: Towards a general framework using PSO as a case study

Improved cooperative <scp>Ant Colony Optimization</scp> for the solution of binary combinatorial optimization applications

Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells

Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants

Assessment of Prediction Uncertainty Quantification Methods in Systems Biology

Global Optimization Approach for Parameter Estimation in Stochastic Dynamic Models of Biosystems

Improving dynamic predictions with ensembles of observable models

IDESS: a toolbox for identification and automated design of stochastic gene circuits

Automated Design of Synthetic Gene Circuits in the Presence of Molecular Noise

Distilling identifiable and interpretable dynamic models from biological data

Parallel ant colony optimization for the training of cell signaling networks

OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production

OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production

An efficient ant colony optimization framework for HPC environments

An efficient ant colony optimization framework for HPC environments

Automated design of synthetic biocircuits in the stochastic regime

Collaborators (6)

Natalio Krasnogor

Manuel Pájaro Diéguez

Bela Novak

Alejandro F. Villaverde

Shouyong Jiang

Patricia González

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