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A Parameter Estimation Method for Multiscale Models of Hepatitis C Virus Dynamics.

Vladimir Reinharz1, Alexander Churkin2, Stephanie Lewkiewicz3

  • 1Department of Computer Science, Ben-Gurion University, Beersheba, Israel.

Bulletin of Mathematical Biology
|July 25, 2019
PubMed
Summary
This summary is machine-generated.

Estimating parameters in complex mathematical models, like those for hepatitis C virus dynamics, is challenging. This study introduces a novel method to directly prepare multiscale model equations for user-controlled parameter estimation, enhancing flexibility and applicability.

Keywords:
Differential equationsHepatitis C virusMultiscale modelsParameter estimation

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Area of Science:

  • Mathematical Biology
  • Computational Virology
  • Systems Biology

Background:

  • Mathematical models, particularly those involving differential equations, necessitate accurate parameter estimation.
  • Sophisticated multiscale models, such as those for hepatitis C virus (HCV) dynamics using partial differential equations (PDEs), present unique parameter estimation challenges.
  • Existing methods like analytical approximations, transformation to ordinary differential equations (ODEs), or black-box numerical solutions have limitations in scope, parameter integrity, or user control.

Purpose of the Study:

  • To develop a novel, user-controlled strategy for parameter estimation in multiscale mathematical models.
  • To overcome the limitations of existing parameter estimation methods for complex models like those describing viral dynamics.

Main Methods:

  • Directly manipulating multiscale model equations to prepare them for parameter estimation.
  • Developing a fully coded, user-controlled parameter estimation method.
  • Utilizing a user-friendly simulator to demonstrate the new method's application.

Main Results:

  • A new strategy for parameter estimation in multiscale models has been successfully developed and described.
  • The method allows for direct work on model equations, offering greater user control.
  • Illustrations using a simulator demonstrate the method's practical application and adaptability.

Conclusions:

  • The developed strategy offers a more flexible and controlled approach to parameter estimation for multiscale models.
  • This method can be adapted for multiscale models of other viruses beyond hepatitis C.
  • Enhanced control over parameter estimation improves the reliability and applicability of complex mathematical models in virology and beyond.