Guidelines for benchmarking of optimization approaches for fitting mathematical models

TL;DR

This paper provides tailored guidelines for benchmarking optimization methods in systems biology to improve the reliability and comparability of model fitting approaches.

Contribution

It introduces specific benchmarking guidelines for optimization-based model fitting in systems biology, addressing methodological challenges and promoting robust evaluation.

Findings

Highlights key methodological challenges in optimization for systems biology

Proposes tailored guidelines for unbiased benchmarking

Calls for comprehensive benchmark studies to improve reliability

Abstract

Insufficient performance of optimization approaches for fitting of mathematical models is still a major bottleneck in systems biology. In this manuscript, the reasons and methodological challenges are summarized as well as their impact in benchmark studies. Important aspects for increasing evidence of outcomes of benchmark analyses are discussed. Based on general guidelines for benchmarking in computational biology, a collection of tailored guidelines is presented for performing informative and unbiased benchmarking of optimization-based fitting approaches. Comprehensive benchmark studies based on these recommendations are urgently required for establishing of a robust and reliable methodology for the systems biology community.