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This thesis uses a systems-level approach to study the cellular metabolism, unveiling new mechanisms and responses that were impossible to reach with traditional reductionists procedures.
The results reported here have a potential application in areas like metabolic engineering and disease treatment. They could also be used in determining the accuracy of the gene essentiality of new genome-scale reconstructions.
Different methods and techniques, within the contexts of Systems Biology and the field known as Complex Networks Analysis have been applied in this work to show different features of the robustness of metabolic networks. The specific issues addressed here range from pure topological aspec
ts of the networks themselves to the balance of biochemical fluxes.
List of contents
Cellular Metabolism at the Systems Level.- Methods and Data.- Structural Knockout Cascades in Metabolic Networks.- E ects of Reaction Knockouts on Steady States of Metabolism.- Detection of Evolution and Adaptation Fingerprints in Metabolic Networks.- Assessing FBA Optimal States in the Feasible Flux Phenotypic Space.- Conclusions.
About the author
Oriol Güell holds a Ph.D. in Physical Chemistry from the University of Barcelona, Spain, and has broad experience in the theoretical modelling and the experimental applications of magnetic colloidal dispersions and in the computer modelling of metabolic networks. Currently, his main research focuses on obtaining and applying bio-based polymers and plasticisers and studying their associated physicochemical properties.
Summary
This thesis uses a systems-level approach to study the cellular metabolism, unveiling new mechanisms and responses that were impossible to reach with traditional reductionists procedures.
The results reported here have a potential application in areas like metabolic engineering and disease treatment. They could also be used in determining the accuracy of the gene essentiality of new genome-scale reconstructions.
Different methods and techniques, within the contexts of Systems Biology and the field known as Complex Networks Analysis have been applied in this work to show different features of the robustness of metabolic networks. The specific issues addressed here range from pure topological aspec
ts of the networks themselves to the balance of biochemical fluxes.
