Parameter estimation of complex mathematical models of human physiology using remote simulation distributed in scientific cloud

Author(s):  
Tomas Kulhanek ◽  
Marek Matejak ◽  
Jan Silar ◽  
Jiri Kofranek
Author(s):  
Johnny T. Ottesen ◽  
Mette S. Olufsen ◽  
Jesper K. Larsen

2019 ◽  
Vol 467 ◽  
pp. 87-99 ◽  
Author(s):  
Karen Larson ◽  
Loukas Zagkos ◽  
Mark Mc Auley ◽  
Jason Roberts ◽  
Nikos I. Kavallaris ◽  
...  

2017 ◽  
Author(s):  
Van Kinh Nguyen ◽  
Esteban A. Hernandez-Vargas

AbstractIn recent years, mathematical modeling approaches have played a central role to understand and to quantify mechanisms in different viral infectious diseases. In this approach, biological-based hypotheses are expressed via mathematical relations and then tested based on empirical data. The simulation results can be used to either identify underlying mechanisms, provide predictions on infection outcomes, or evaluate the efficacy of a treatment.Conducting parameter estimation for mathematical models is not an easy task. Here we detail an approach to conduct parameter estimation and to evaluate the results using the free software R. The method is applicable to influenza virus dynamics at different complexity levels, widening experimentalists capabilities in understanding their data. The parameter estimation approach presented here can be also applied to other viral infections or biological applications.


1987 ◽  
Vol 30 (5) ◽  
pp. 1353-1357
Author(s):  
T. C. Bridges ◽  
E. M. Smith ◽  
L. W. Turner

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