| COVID‐19 pandemic‐related lockdown: response time is more important than its strictness G Loewenthal, S Abadi, O Avram, K Halabi, N Ecker, N Nagar, I Mayrose, ... EMBO molecular medicine 12 (11), e13171, 2020 | 57 | 2020 |
| Harnessing machine learning to unravel protein degradation in Escherichia coli N Nagar, N Ecker, G Loewenthal, O Avram, D Ben-Meir, D Biran, E Ron, ... Msystems 6 (1), e01296-20, 2021 | 19 | 2021 |
| Natural language processing approach to model the secretion signal of type III effectors N Wagner, M Alburquerque, N Ecker, E Dotan, B Zerah, MM Pena, ... Frontiers in Plant Science 13, 1024405, 2022 | 9 | 2022 |
| Multiple sequence alignment as a sequence-to-sequence learning problem E Dotan, Y Belinkov, O Avram, E Wygoda, N Ecker, M Alburquerque, ... The Eleventh International Conference on Learning Representations, 2023 | 6 | 2023 |
| A LASSO-based approach to sample sites for phylogenetic tree search N Ecker, D Azouri, B Bettisworth, A Stamatakis, Y Mansour, I Mayrose, ... Bioinformatics 38 (Supplement_1), i118-i124, 2022 | 5 | 2022 |
| A machine-learning-based alternative to phylogenetic bootstrap N Ecker, D Huchon, Y Mansour, I Mayrose, T Pupko Bioinformatics 40 (Supplement_1), i208-i217, 2024 | 4 | 2024 |
| An Approximate Bayesian Computation Approach for Modeling Genome Rearrangements A Moshe, E Wygoda, N Ecker, G Loewenthal, O Avram, O Israeli, ... Molecular Biology and Evolution 39 (11), msac231, 2022 | 3 | 2022 |
| BetaAlign: a deep learning approach for multiple sequence alignment E Dotan, E Wygoda, N Ecker, M Alburquerque, O Avram, Y Belinkov, ... bioRxiv, 2024.03. 24.586462, 2024 | 1 | 2024 |
| Harnessing machine translation methods for sequence alignment E Dotan, Y Belinkov, O Avram, E Wygoda, N Ecker, M Alburquerque, ... bioRxiv, 2022.07. 22.501063, 2022 | | 2022 |
