**5. Conclusions**

In this work, we present a population-based framework for parameter identification of biological networks described as dynamic models. The obtained results indicate the grea<sup>t</sup> potential of population-based optimization methods in the field of biology and biochemistry. In the case of relatively low computational costs of obtaining an evaluation of parameters, the population-based methods seem to be sufficient to solve the parameter identification problem. Moreover, our results for applying surrogate models to the optimizers can be highly effective (i.e., speeding up convergence). It is a known fact (e.g., see [31,38]), nevertheless, we believe that the optimization with surrogate models has a grea<sup>t</sup> future and should be further investigated. For instance, considering other classes of surrogate models like Gaussian processes or (Bayesian) neural networks opens new opportunities and research questions worth following.

Additionally, the development of our framework in Python, an open-source platform, simplifies its distribution and enables its use on most operating systems. POPI4SB is easyto-use and since the code is freely available, it constitutes a platform for developing new population-based optimizers. Therefore, the proposed framework can be relatively easily extended and serve for future research.

**Author Contributions:** Conceptualization, E.W.-T.; methodology, E.W.-T. and J.M.T.; software, J.M.T.; validation, E.W.-T. and J.M.T.; formal analysis, E.W.-T. and J.M.T.; investigation, E.W.-T. and J.M.T.; resources, E.W.-T. and J.M.T.; writing—original draft preparation, E.W.-T. and J.M.T.; writing—review and editing, A.E.E. and S.B.; visualization, J.M.T.; supervision, S.B.; project administration, E.W.-T. All authors have read and agreed to the published version of the manuscript.

**Funding:** EW-T was financed by a gran<sup>t</sup> within Mobilno´s´c Plus V from the Polish Ministry of Science and Higher Education (Grant 1639/MOB/V/2017/0).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The code is available at: https://github.com/jmtomczak/popi4sb.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
