Unsupervised Machine Learning for Adaptive Immune Receptors with immuneML: use case 2
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2026
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| _version_ | 1866901911223926784 |
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| author | Pavlović, Milena Würtzen, Charlotte Kanduri, Chakravarthi Mamica, Maria Scheffer, Lonneke Lund-Andersen, Christin Gubatan, John Mark Ullmann, Theresa Greiff, Victor Sandve, Geir Kjetil |
| author_facet | Pavlović, Milena Würtzen, Charlotte Kanduri, Chakravarthi Mamica, Maria Scheffer, Lonneke Lund-Andersen, Christin Gubatan, John Mark Ullmann, Theresa Greiff, Victor Sandve, Geir Kjetil |
| contents | <p>This upload contains all the results from use case 2 on simulated data of the manuscript<strong> </strong><em>Unsupervised Machine Learning for Adaptive Immune Receptors with immuneML</em>. Specifically, it includes all the analysis specification files for immuneML and the immuneML output.</p> <p>The analyses were performed on 4 simulated datasets.</p> <p>For full information on how to reproduce these results, see the GitHub repository: https://github.com/immuneML/immuneML-unsupervisedML-usecases.</p> <p>immuneML GitHub repository: https://github.com/uio-bmi/immuneML</p> <p>The analyses are compatible with the latest immuneML version at the time of submission (3.0.21).</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19565450 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Unsupervised Machine Learning for Adaptive Immune Receptors with immuneML: use case 2 Pavlović, Milena Würtzen, Charlotte Kanduri, Chakravarthi Mamica, Maria Scheffer, Lonneke Lund-Andersen, Christin Gubatan, John Mark Ullmann, Theresa Greiff, Victor Sandve, Geir Kjetil <p>This upload contains all the results from use case 2 on simulated data of the manuscript<strong> </strong><em>Unsupervised Machine Learning for Adaptive Immune Receptors with immuneML</em>. Specifically, it includes all the analysis specification files for immuneML and the immuneML output.</p> <p>The analyses were performed on 4 simulated datasets.</p> <p>For full information on how to reproduce these results, see the GitHub repository: https://github.com/immuneML/immuneML-unsupervisedML-usecases.</p> <p>immuneML GitHub repository: https://github.com/uio-bmi/immuneML</p> <p>The analyses are compatible with the latest immuneML version at the time of submission (3.0.21).</p> |
| title | Unsupervised Machine Learning for Adaptive Immune Receptors with immuneML: use case 2 |
| url | https://doi.org/10.5281/zenodo.19565450 |