%0 Journal Article %1 Hafner2009Glocal %A Hafner, Marc %A Koeppl, Heinz %A Hasler, Martin %A Wagner, Andreas %D 2009 %I Public Library of Science %J PLOS Computational Biology %K robustness sensitivity-analysis %N 10 %P 1-10 %R 10.1371/journal.pcbi.1000534 %T ‘Glocal’ Robustness Analysis and Model Discrimination for Circadian Oscillators %U https://doi.org/10.1371/journal.pcbi.1000534 %V 5 %X Author Summary Robustness is an intrinsic property of many biological systems. To quantify the robustness of a model that represents such a system, two approaches exist: global methods assess the volume in parameter space that is compliant with the proper functioning of the system; and local methods, in contrast, study the model for a given parameter set and determine its robustness. Local methods are fundamentally biased due to the a priori choice of a particular parameter set. Our ‘glocal’ analysis combines the two complementary approaches and provides an objective measure of robustness. We apply this method to two prominent, recent models of the cyanobacterial circadian oscillator. Our results allow discriminating the two models based on this analysis: both global and local measures of robustness favor one of the two models. The ‘glocal’ method also identifies key factors that influence robustness. For instance, we find that in both models the most fragile reactions are the ones that affect the concentration of the feedback component.

@article{Hafner2009Glocal, abstract = {Author Summary Robustness is an intrinsic property of many biological systems. To quantify the robustness of a model that represents such a system, two approaches exist: global methods assess the volume in parameter space that is compliant with the proper functioning of the system; and local methods, in contrast, study the model for a given parameter set and determine its robustness. Local methods are fundamentally biased due to the a priori choice of a particular parameter set. Our ‘glocal’ analysis combines the two complementary approaches and provides an objective measure of robustness. We apply this method to two prominent, recent models of the cyanobacterial circadian oscillator. Our results allow discriminating the two models based on this analysis: both global and local measures of robustness favor one of the two models. The ‘glocal’ method also identifies key factors that influence robustness. For instance, we find that in both models the most fragile reactions are the ones that affect the concentration of the feedback component.}, added-at = {2019-08-05T07:50:05.000+0200}, author = {Hafner, Marc and Koeppl, Heinz and Hasler, Martin and Wagner, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2750ffd80a61b6ec2a76ec97aef77442f/karthikraman}, description = {‘Glocal’ Robustness Analysis and Model Discrimination for Circadian Oscillators}, doi = {10.1371/journal.pcbi.1000534}, interhash = {12d4a3a812e3164ad552c56beee97951}, intrahash = {750ffd80a61b6ec2a76ec97aef77442f}, journal = {PLOS Computational Biology}, keywords = {robustness sensitivity-analysis}, month = {10}, number = 10, pages = {1-10}, publisher = {Public Library of Science}, timestamp = {2019-08-05T07:50:05.000+0200}, title = {‘Glocal’ Robustness Analysis and Model Discrimination for Circadian Oscillators}, url = {https://doi.org/10.1371/journal.pcbi.1000534}, volume = 5, year = 2009 }