| Accurate structure prediction of biomolecular interactions with AlphaFold 3 J Abramson, J Adler, J Dunger, R Evans, T Green, A Pritzel, ... Nature, 1-3, 2024 | 2185 | 2024 |
| Automated Gleason grading of prostate cancer tissue microarrays via deep learning E Arvaniti, KS Fricker, M Moret, N Rupp, T Hermanns, C Fankhauser, ... Scientific reports 8 (1), 12054, 2018 | 443 | 2018 |
| GM-CSF and CXCR4 define a T helper cell signature in multiple sclerosis E Galli, FJ Hartmann, B Schreiner, F Ingelfinger, E Arvaniti, M Diebold, ... Nature medicine 25 (8), 1290-1300, 2019 | 189 | 2019 |
| Sensitive detection of rare disease-associated cell subsets via representation learning E Arvaniti, M Claassen Nature communications 8 (1), 14825, 2017 | 163 | 2017 |
| Similarities and differences of blood N-glycoproteins in five solid carcinomas at localized clinical stage analyzed by SWATH-MS T Sajic, Y Liu, E Arvaniti, S Surinova, EG Williams, R Schiess, ... Cell reports 23 (9), 2819-2831. e5, 2018 | 44 | 2018 |
| Coupling weak and strong supervision for classification of prostate cancer histopathology images E Arvaniti, M Claassen arXiv preprint arXiv:1811.07013, 2018 | 22 | 2018 |
| Identification of ALP+/CD73+ defining markers for enhanced osteogenic potential in human adipose-derived mesenchymal stromal cells by mass cytometry DD Canepa, EA Casanova, E Arvaniti, V Tosevski, S Märsmann, ... Stem Cell Research & Therapy 12, 1-16, 2021 | 19 | 2021 |
| Automated Gleason grading of prostate cancer tissue microarrays via deep learning. Sci Rep. 2018; 8 (1): 12054 E Arvaniti, KS Fricker, M Moret, N Rupp, T Hermanns, C Fankhauser, ... Preprint not peer reviewed, 0 | 12 | |
| Author Correction: Automated Gleason grading of prostate cancer tissue microarrays via deep learning E Arvaniti, KS Fricker, M Moret, N Rupp, T Hermanns, C Fankhauser, ... Scientific reports 9, 2019 | 10 | 2019 |
| Polarizable coarse‐grained models for molecular dynamics simulation of liquid cyclohexane OM Szklarczyk, E Arvaniti, WF van Gunsteren Journal of computational chemistry 36 (17), 1311-1321, 2015 | 9 | 2015 |
| Automated random model-based testing of stateful systems E Arvaniti Diploma thesis, National Technical University of Athens, School of …, 2011 | 7 | 2011 |
| Markov network structure learning via ensemble-of-forests models E Arvaniti, M Claassen arXiv preprint arXiv:1312.4710, 2013 | 5 | 2013 |
| Proxy-based zero-shot entity linking by effective candidate retrieval M Wiatrak, E Arvaniti, A Brayne, J Vetterle, A Sim arXiv preprint arXiv:2301.13318, 2023 | 3 | 2023 |
| Author correction: Automated gleason grading of prostate cancer tissue microarrays via deep learning E Arvaniti, KS Fricker, M Moret, N Rupp, T Hermanns, C Fankhauser, ... Scientific Reports 11, 2021 | 3 | 2021 |
| Automated Gleason grading of prostate cancer tissue microarrays via deep learning (vol 8, 12054, 2018) E Arvaniti, KS Fricker, M Moret, N Rupp, T Hermanns, C Fankhauser, ... SCIENTIFIC REPORTS 9, 2019 | 2 | 2019 |
| Supervised learning on synthetic data for reverse engineering gene regulatory networks from experimental time-series S Ganscha, V Fortuin, M Horn, E Arvaniti, M Claassen bioRxiv, 356477, 2018 | 2 | 2018 |
| Automated Gleason grading of whole slide prostatectomy images J Grogg, E Arvaniti, S Gretser, K Smith, T Sulser, T Hermanns, PJ Wild, ... European Urology Open Science 19, e581, 2020 | | 2020 |
| Automated Gleason grading of prostate cancer via deep learning E Arvaniti, KS Fricker, M Moret, N Rupp, C Fankhauser, T Hermanns, ... European Urology Supplements 17 (14), e3020-e3021, 2018 | | 2018 |
| Identifying Disease-Associated Patterns in Single Cell-Resolved Data by Weakly-Supervised Learning E Arvaniti ETH Zurich, 2018 | | 2018 |
| Navigation Area R Aebersold, M Pestalozzi, L Gillet, P Pedrioli, S Amon, P Blattmann, ... Genome, 01, 2017 | | 2017 |
