Search results

Chen, D.; Hartout, P.; Pellizzoni, P.; Oliver, C.; Borgwardt, K.: Endowing protein language models with structural knowledge. arXiv: Condensed Matter-Materials Science (2024)

Karia, D.; Koh, A. F.; Yang, W.; Cushing, V. I.; Basanta, B.; Mihaylov, D. B.; Khavnekar, S.; Vyroubal, O.; Malínský, M.; Sháněl, O. et al.; Doležal, V.; Plitzko, J. M.; Yu, L.; Lander, G. C.; Aricescu, A. R.; Greber, B. J.; Kotecha, A.: Sub-3 Å resolution protein structure determination by single-particle cryo-EM at 100 keV. bioRxiv: the preprint server for biology (2024)

Muzio, G.; Adamer, M.; Fernandez, L.; Borgwardt, K.; Avican, K.: Bacterial protein function prediction via multimodal deep learning. bioRxiv: the preprint server for biology (2024)

Sachweh, J.; Börmel, M.; Klumpe, S.; Becker, A.; Taniguchi, R.; Kubańska, M. A.; Pintschovius, V.; Kaindl, E.; Plitzko, J. M.; Wilfling, F. et al.; Beck, M.; Hampoelz, B.: The small GTPase Ran defines Nuclear Pore Complex Asymmetry. bioRxiv: the preprint server for biology (2024)

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

Verkuil, R.; Kabeli, O.; Du, Y.; Wicky, B. I. M.; Milles, L. F.; Dauparas, J.; Baker, D.; Ovchinnikov, S.; Sercu, T.; Rives, A.: Language models generalize beyond natural proteins. bioRxiv (2022)

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

Moor, M.; Bennet, N.; Plecko, D.; Horn, M.; Rieck, B.; Meinshausen, N.; Bühlmann, P.; Borgwardt, K.: Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. arXiv (2021)

Moor, M.; Horn, M.; Bock, C.; Borgwardt, K.; Rieck, B.: Path Imputation Strategies for Signature Models of Irregular Time Series. arXiv (2020)

Ramirez-Diaz, D. A.; Merino-Salomon, A.; Heymann, M.; Schwille, P.: Bidirectional FtsZ filament treadmilling promotes membrane constriction via torsional stress. bioRxiv, 587790 (2019)

Ganzinger, K. A.; Merino-Salomon, A.; Garcia-Soriano, D.; Butterfield, N.; Butterfield, N. A.; Litschel, T.; Siedler, F.; Schwille, P.: Microfluidic trapping of vesicles reveals membrane-tension dependent FtsZ cytoskeletal re-organisation. bioRxiv, 791459 (2019)

Milles, L. F.; Gaub, H. E.: Is mechanical receptor ligand dissociation driven by unfolding or unbinding? bioRxiv (2019)

Bauer, M. S.; Milles, L. F.; Sedlak, S. M.; Gaub, H. E.: Monomeric streptavidin: a versatile regenerative handle for force spectroscopy. bioRxiv (2018)