{"publication_status":"published","OA_type":"gold","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"publication_identifier":{"eissn":["2056-7189"]},"year":"2026","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}],"doi":"10.1038/s41540-026-00648-9","acknowledgement":"This work was supported by the German Federal Ministry of Education and Research (BMBF) (EMUNE/031L0293C), the European Union via the ERC grant INTEGRATE, grant agreement number 101126146, and under Germany’s Excellence Strategy by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (EXC 2047—390685813, EXC 2151—390873048, FOR5775 — 533863915, and 524747443), the University of Bonn via the Schlegel Professorship of J.H., and the returning experts fellowship of the Ministry of Innovation, Science, and Research of North-Rhine-Westphalia (AZ: 421-8.03.03.02-137069). J.M. is a member of the Nanofabrication Facility and is supported by the Institute of Science and Technology Austria. E.K. acknowledges the TRA Life and Health (University of Bonn) as part of the Excellence Strategy of the federal and state governments. The authors thank Laeschkir Würthner for his insightful comments on the implementation of the authors’ model. The views and opinions expressed are those of the authors only and do not necessarily reflect those of the funding agencies. Parts of Fig. 1 were created using BioRender. Open Access funding enabled and organized by Projekt DEAL.","publication":"npj Systems Biology and Applications","date_created":"2026-02-16T10:44:31Z","_id":"21231","file":[{"file_size":10217687,"access_level":"open_access","creator":"dernst","checksum":"99b2e6bbaaedf45f22e07751948669f5","date_created":"2026-02-23T10:09:03Z","success":1,"relation":"main_file","file_id":"21346","content_type":"application/pdf","date_updated":"2026-02-23T10:09:03Z","file_name":"2026_npjSysBioApp_Arruda.pdf"}],"quality_controlled":"1","article_processing_charge":"Yes (via OA deal)","month":"02","author":[{"last_name":"Arruda","full_name":"Arruda, Jonas","first_name":"Jonas"},{"last_name":"Alamoudi","full_name":"Alamoudi, Emad","first_name":"Emad"},{"first_name":"Robert","full_name":"Mueller, Robert","last_name":"Mueller"},{"full_name":"Vaisband, Marc","first_name":"Marc","last_name":"Vaisband"},{"last_name":"Molkenbur","first_name":"Ronja","full_name":"Molkenbur, Ronja"},{"first_name":"Jack","orcid":"0000-0001-5145-4609","full_name":"Merrin, Jack","id":"4515C308-F248-11E8-B48F-1D18A9856A87","last_name":"Merrin"},{"full_name":"Kiermaier, Eva","first_name":"Eva","last_name":"Kiermaier"},{"full_name":"Hasenauer, Jan","first_name":"Jan","last_name":"Hasenauer"}],"article_type":"original","oa_version":"Published Version","title":"Simulation-based inference of cell migration dynamics in complex spatial environments","external_id":{"pmid":["41611727"]},"article_number":"20","date_published":"2026-02-05T00:00:00Z","DOAJ_listed":"1","abstract":[{"lang":"eng","text":"To assess cell migration in complex spatial environments, microfabricated chips, such as mazes and pillar forests, are routinely used to impose spatial and mechanical constraints, and cell trajectories are followed within these structures by advanced imaging techniques. In systems mechanobiology, computational models serve as essential tools to uncover how physical geometry influences intracellular dynamics; however, decoding such complex behaviors requires advanced inference techniques. Here, we integrated experimental observations of dendritic cell migration in a geometrically constrained microenvironment into a Cellular Potts model. We demonstrated that these spatial constraints modulate the motility dynamics, including speed and directional changes. We show that classical summary statistics, such as mean squared displacement and turning angle distributions, can resolve key mechanistic features but fail to extract richer spatiotemporal patterns, limiting accurate parameter inference. To solve this, we applied neural posterior estimation with in-the-loop learning of summary features. This learned summary representation of the data enables robust and flexible parameter inference, providing a data-driven framework for model calibration and advancing quantitative analysis of cell migration in structured microenvironments."}],"file_date_updated":"2026-02-23T10:09:03Z","citation":{"ista":"Arruda J, Alamoudi E, Mueller R, Vaisband M, Molkenbur R, Merrin J, Kiermaier E, Hasenauer J. 2026. Simulation-based inference of cell migration dynamics in complex spatial environments. npj Systems Biology and Applications. 12, 20.","chicago":"Arruda, Jonas, Emad Alamoudi, Robert Mueller, Marc Vaisband, Ronja Molkenbur, Jack Merrin, Eva Kiermaier, and Jan Hasenauer. “Simulation-Based Inference of Cell Migration Dynamics in Complex Spatial Environments.” <i>Npj Systems Biology and Applications</i>. Springer Nature, 2026. <a href=\"https://doi.org/10.1038/s41540-026-00648-9\">https://doi.org/10.1038/s41540-026-00648-9</a>.","short":"J. Arruda, E. Alamoudi, R. Mueller, M. Vaisband, R. Molkenbur, J. Merrin, E. Kiermaier, J. Hasenauer, Npj Systems Biology and Applications 12 (2026).","apa":"Arruda, J., Alamoudi, E., Mueller, R., Vaisband, M., Molkenbur, R., Merrin, J., … Hasenauer, J. (2026). Simulation-based inference of cell migration dynamics in complex spatial environments. <i>Npj Systems Biology and Applications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41540-026-00648-9\">https://doi.org/10.1038/s41540-026-00648-9</a>","mla":"Arruda, Jonas, et al. “Simulation-Based Inference of Cell Migration Dynamics in Complex Spatial Environments.” <i>Npj Systems Biology and Applications</i>, vol. 12, 20, Springer Nature, 2026, doi:<a href=\"https://doi.org/10.1038/s41540-026-00648-9\">10.1038/s41540-026-00648-9</a>.","ama":"Arruda J, Alamoudi E, Mueller R, et al. Simulation-based inference of cell migration dynamics in complex spatial environments. <i>npj Systems Biology and Applications</i>. 2026;12. doi:<a href=\"https://doi.org/10.1038/s41540-026-00648-9\">10.1038/s41540-026-00648-9</a>","ieee":"J. Arruda <i>et al.</i>, “Simulation-based inference of cell migration dynamics in complex spatial environments,” <i>npj Systems Biology and Applications</i>, vol. 12. Springer Nature, 2026."},"ddc":["570"],"day":"05","OA_place":"publisher","oa":1,"intvolume":"        12","type":"journal_article","department":[{"_id":"NanoFab"}],"pmid":1,"publisher":"Springer Nature","PlanS_conform":"1","status":"public","date_updated":"2026-02-23T10:10:10Z","volume":12,"has_accepted_license":"1","scopus_import":"1"}