ConSurf: using evolutionary data to raise testable hypotheses about protein function G Celniker, G Nimrod, H Ashkenazy, F Glaser, E Martz, I Mayrose, ... Israel Journal of Chemistry 53 (3‐4), 199-206, 2013 | 603 | 2013 |
Deep sequencing analysis of viral infection and evolution allows rapid and detailed characterization of viral mutant spectrum O Isakov, AV Bordería, D Golan, A Hamenahem, G Celniker, L Yoffe, ... Bioinformatics 31 (13), 2141-2150, 2015 | 70 | 2015 |
Patch Finder Plus (PFplus): a web server for extracting and displaying positive electrostatic patches on protein surfaces S Shazman, G Celniker, O Haber, F Glaser, Y Mandel-Gutfreund Nucleic acids research 35 (suppl_2), W526-W530, 2007 | 65 | 2007 |
Transfer learning for user action identication in mobile apps via encrypted trafc analysis E Grolman, A Finkelshtein, R Puzis, A Shabtai, G Celniker, Z Katzir, ... IEEE Intelligent Systems 33 (2), 40-53, 2018 | 41 | 2018 |
Seasonal genetic drift of human influenza A virus quasispecies revealed by deep sequencing C Barbezange, L Jones, H Blanc, O Isakov, G Celniker, V Enouf, ... Frontiers in microbiology 9, 2596, 2018 | 39 | 2018 |
Rare genetic variants in Tunisian Jewish patients suffering from age-related macular degeneration E Pras, D Kristal, N Shoshany, D Volodarsky, I Vulih, G Celniker, O Isakov, ... Journal of Medical Genetics 52 (7), 484-492, 2015 | 22 | 2015 |
Crowdfunding effort identifies the causative mutation in a patient with nystagmus, microcephaly, dystonia and hypomyelination O Isakov, D Lev, L Blumkin, G Celniker, E Leshinsky-Silver, N Shomron Journal of genetics and genomics= Yi chuan xue bao 42 (2), 79-81, 2015 | 16 | 2015 |
System and method for generating data sets for learning to identify user actions Z Katzir, G Celnicker, H Kovetz US Patent 10,491,609, 2019 | 13 | 2019 |
SMYD1 is the underlying gene for the AnWj‐negative blood group phenotype V Yahalom, N Pillar, Y Zhao, S Modan, M Fang, L Yosephi, O Asher, ... European Journal of Haematology 101 (4), 496-501, 2018 | 9 | 2018 |
Validation of an automatic tagging system for identifying respiratory and hemodynamic deterioration events in the intensive care unit O Chen, AM Lipsky, A Forgacs, G Celniker, CM Lilly, IM Pessach Healthcare informatics research 27 (3), 241-248, 2021 | 6 | 2021 |
System and method for applying transfer learning to identification of user actions R Puzis, A Shabtai, G Celniker, L Rosenfeld, Z Katzir, E Grolman US Patent App. 15/911,223, 2018 | 6 | 2018 |
Methods and systems for genome comparison N Shomron, O Isakov, G Celniker, N Pillar US Patent App. 15/127,417, 2017 | 6 | 2017 |
Application of machine learning models to biomedical and information system signals from critically ill adults CM Lilly, D Kirk, IM Pessach, G Lotun, O Chen, A Lipsky, I Lieder, ... Chest 165 (5), 1139-1148, 2024 | 1 | 2024 |
System and method for eye-gaze direction-based pre-training of neural networks RM Hecht, O Tsimhoni, D Levi, S Oron, A Forgacs, O Rahamim, ... US Patent App. 18/489,338, 2024 | | 2024 |
Gaze Pre-Train For Improving Disparity Estimation Networks RM Hecht, O Rahamim, S Oron, A Forgacs, G Celniker, D Levi, ... ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | | 2023 |
System and method for generating data sets for learning to identify user actions Z Katzir, G Celniker, H Kovetz US Patent 11,303,652, 2022 | | 2022 |
171: USING ARTIFICIAL INTELLIGENCE MODELS TO PREDICT DETERIORATION IN CRITICALLY ILL COVID-19 PATIENTS RK Lerner, N Baharav, O Chen, A Levi, A Lipsky, G Celniker, I Pessach Critical Care Medicine 50 (1), 69, 2022 | | 2022 |
462: USING ARTIFICIAL INTELLIGENCE TO PREDICT WHICH PATIENTS ARE NOT GOING TO DETERIORATE I Pessach, O Chen, O Rosenberg, G Celniker, A Lipsky, A Forgacs, C Lilly, ... Critical Care Medicine 50 (1), 221, 2022 | | 2022 |
460: DEVELOPMENT OF AI-BASED MODELS FOR PREDICTING LIFE-THREATENING EVENTS IN CRITICALLY ILL PATIENTS I Pessach, D Kirk, O Chen, A Lipsky, I Lieder, G Celniker, C Lilly, E Cucchi, ... Critical Care Medicine 50 (1), 220, 2022 | | 2022 |
System and method for generating data sets for learning to identify user actions Z Katzir, G Celnicker, H Kovetz US Patent 10,944,763, 2021 | | 2021 |