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Area of Science:

  • Systems biology
  • Computational biology
  • Mathematical modeling

Background:

  • Optimization-based approaches are crucial for fitting mathematical models in systems biology.
  • Current methods face performance limitations, hindering progress in the field.
  • Methodological challenges in existing approaches impact the reliability of benchmark studies.

Framework:

  • Summarizes reasons and methodological challenges in optimization-based model fitting.
  • Discusses aspects for increasing the level of evidence in benchmark results.
  • Presents tailored guidelines for informative and unbiased benchmarking of fitting approaches.

Implementation:

  • Guidelines are based on general principles of benchmarking in computational biology.
  • Focuses on creating unbiased and informative benchmark studies.
  • Aims to address the lack of robust methodology in systems biology.

Implications:

  • Comprehensive benchmark studies are needed to validate these recommendations.
  • Establishes a foundation for a robust and reliable methodology for systems biology.
  • Enhances the credibility and reproducibility of systems biology research.