Publications

Adamer, M. F.; Roellin, E.; Bourguignon, L.; Borgwardt, K.: SIMBSIG: similarity search and clustering for biobank-scale data. Bioinformatics 39 (1), btac829 (2022)

Adamer, M. F.; Brüningk, S. C.; Tejada-Arranz, A.; Estermann, F.; Basler, M.; Borgwardt, K.: reComBat: batch-effect removal in large-scale multi-source gene-expression data integration. Bioinformatics Advances 2 (1), vbac071 (2022)

Brüningk, S. C.; Klatt, J.; Stange, M.; Mari, A.; Brunner, M.; Roloff, T.-C.; Seth-Smith, H. M. B.; Schweitzer, M.; Leuzinger, K.; Søgaard, K. K. et al.; Albertos Torres, D.; Gensch, A.; Schlotterbeck, A.-K.; Nickel, C. H.; Ritz, N.; Heininger, U.; Bielicki, J.; Rentsch, K.; Fuchs, S.; Bingisser, R.; Siegemund, M.; Pargger, H.; Ciardo, D.; Dubuis, O.; Buser, A.; Tschudin-Sutter, S.; Battegay, M.; Schneider-Sliwa, R.; Borgwardt, K. M.; Hirsch, H. H.; Egli, A.: Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area. Virus Evolution 8 (1), veac002 (2022)

Chen, D.; O’Bray, L.; Borgwardt, K.: Structure-Aware Transformer for Graph Representation Learning. Proceedings of the 39th International Conference on Machine Learning (ICML 2022) 162, pp. 3469 - 3489 (2022)

Fan, B.; Klatt, J.; Moor, M. M.; Daniels, L. A.; Swiss Pediatric Sepsis, S.; Agyeman, P. K. A.; Berger, C.; Giannoni, E.; Stocker, M.; Posfay-Barbe, K. M. et al.; Heininger, U.; Bernhard-Stirnemann, S.; Niederer-Loher, A.; Kahlert, C. R.; Natalucci, G.; Relly, C.; Riedel, T.; Aebi, C.; Schlapbach, L. J.; Sanchez-Pinto, L. N.; Agyeman, P. K. A.; Schlapbach, L. J.; Borgwardt, K.: Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients. Bioinformatics 38 (Supplement_1), pp. i101 - i108 (2022)

O'Bray*, L.; Horn*, M.; Rieck*, B.; Borgwardt*, K.; (* = equal contribution): Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. Tenth International Conference on Learning Representations (ICLR 2022) (2022)

Weis, C.; Cuénod, A.; Rieck, B.; Dubuis, O.; Graf, S.; Lang, C.; Oberle, M.; Brackmann, M.; Søgaard, K. K.; Osthoff, M. et al.; Borgwardt*, K.; Egli*, A.; (* = equal contribution): Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning. Nature Medicine 28 (1), pp. 164 - 174 (2022)

Oliver, C.; Chen, D.; Mallet, V.; Philippopoulos, P.; Borgwardt, K.: Approximate Network Motif Mining Via Graph Learning. (2022)

Hornauer, P.; Prack, G.; Anastasi, N.; Ronchi, S.; Kim, T.; Donner, C.; Fiscella, M.; Borgwardt, K.; Taylor, V.; Jagasia, R. et al.; Roqueiro, D.; Hierlemann, A.; Schröter, M.: Downregulating α-synuclein in iPSC-derived dopaminergic neurons mimics electrophysiological phenotype of the A53T mutation. (2022)

Weis, C.; Rieck, B.; Balzer, S.; Cuénod, A.; Egli, A.; Borgwardt, K.: Improved MALDI-TOF MS based antimicrobial resistance prediction through hierarchical stratification. (2022)