publications.html

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title: Publications
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The EMUNE project has resulted in the following publications:

<p><b>Compositional amortized inference for large-scale hierarchical Bayesian models</b>.<br />
Arruda, J., Pandey, V., Sherry, C., Barroso, M., Intes, X., Hasenauer, J., & Radev, S. T. (2025).<br />
<a href="https://doi.org/10.48550/arXiv.2505.14429">Link</a></p>

<p><b>A latent cardiomyocyte regeneration potential in human heart disease</b>.<br />
Derks, W., et al. (2025).<br />
<a href="https://doi.org/10.1161/CIRCULATIONAHA.123.067156">Link</a></p>

<p><b>Developmental beta-cell death orchestrates the islet’s inflammatory milieu by regulating immune system crosstalk</b>.<br />
Akhtar, M. N., et al. (2025).<br />
<a href="https://doi.org/10.1038/s44318-024-00332-w">Link</a></p>

<p><b>An amortized approach to non-linear mixed-effects modeling based on neural posterior estimation</b>.<br />
Arruda, J., Schälte, Y., Peiter, C., Teplytska, O., Jaehde, U., & Hasenauer, J. (2024).<br />
<a href="https://proceedings.mlr.press/v235/arruda24a.html">Link</a></p>

<p><b>Universal differential equations for systems biology: Current state and open problems</b>.<br />
Philipps, M., Schmid, N., & Hasenauer, J. (2024).<br />
<a href="https://doi.org/10.1101/2024.11.29.626122">Link</a></p>

<p><b>Efficient parameter estimation for ODE models of cellular processes using semi-quantitative data</b>.<br />
Dorešić, D., Grein, S., & Hasenauer, J. (2024).<br />
<a href="https://doi.org/10.1093/bioinformatics/btae210">Link</a></p>

<p><b>Tailoring COVID-19 Vaccination Strategies in High-Seroprevalence Settings: Insights from Ethiopia</b>.<br />
Gudina, E. K., et al. (2024).<br />
<a href="https://doi.org/10.3390/vaccines12070745">Link</a></p>

<p><b>A wall-time minimizing parallelization strategy for approximate Bayesian computation</b>.<br />
Alamoudi, E., et al. (2024).<br />
<a href="https://doi.org/10.1371/journal.pone.0294015">Link</a></p>

<p><b>Missing data in amortized simulation-based neural posterior estimation</b>.<br />
Wang, Z., Hasenauer, J., & Schälte, Y. (2024).<br />
<a href="https://doi.org/10.1371/journal.pcbi.1012184">Link</a></p>

<p><b>Collective cell migration due to guidance-by-followers is robust to multiple stimuli</b>.<br />
Müller, R., Boutillon, A., Jahn, D., Starruß, J., David, N. B., & Brusch, L. (2023).<br />
<a href="https://doi.org/10.3389/fams.2023.1163583">Link</a></p>

<p><b>FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes</b>.<br />
Alamoudi, E., et al. (2023).<br />
<a href="https://doi.org/10.1093/bioinformatics/btad674">Link</a></p>

<p><b>Accessibility of covariance information creates vulnerability in Federated Learning frameworks</b>.<br />
Huth, M., et al. (2023).<br />
<a href="https://doi.org/10.1093/bioinformatics/btad531">Link</a></p>

<p><b>Informative and adaptive distances and summary statistics in sequential approximate Bayesian computation</b>.<br />
Schälte, Y., & Hasenauer, J. (2023).<br />
<a href="https://doi.org/10.1371/journal.pone.0285836">Link</a></p>

<p><b>pyABC: Efficient and robust easy-to-use approximate Bayesian computation</b>.<br />
Schälte, Y., Klinger, E., Alamoudi, E., & Hasenauer, J. (2022).<br />
<a href="https://doi.org/10.21105/joss.04304">Link</a></p>