| Discovering protein drug targets using knowledge graph embeddings SK Mohamed, V Nováček, A Nounu Bioinformatics 36 (2), 603-610, 2020 | 236 | 2020 |
| Biological applications of knowledge graph embedding models SK Mohamed, A Nounu, V Nováček Briefings in bioinformatics 22 (2), 1679-1693, 2021 | 142 | 2021 |
| Biokg: A knowledge graph for relational learning on biological data B Walsh, SK Mohamed, V Nováček Proceedings of the 29th ACM International Conference on Information …, 2020 | 82 | 2020 |
| Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models E Muñoz, V Nováček, PY Vandenbussche Briefings in bioinformatics 20 (1), 190-202, 2019 | 78 | 2019 |
| Regularizing knowledge graph embeddings via equivalence and inversion axioms P Minervini, L Costabello, E Muñoz, V Nováček, PY Vandenbussche Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 69 | 2017 |
| Predicting polypharmacy side-effects using knowledge graph embeddings V Nováček, SK Mohamed AMIA Summits on Translational Science Proceedings 2020, 449, 2020 | 48 | 2020 |
| Loss Functions in Knowledge Graph Embedding Models. SK Mohamed, V Novácek, PY Vandenbussche, E Muñoz DL4KG@ ESWC 2377, 1-10, 2019 | 48 | 2019 |
| Drug target discovery using knowledge graph embeddings SK Mohamed, A Nounu, V Nováček Proceedings of the 34th ACM/SIGAPP symposium on applied computing, 11-18, 2019 | 43 | 2019 |
| An artificial intelligence-based tool for data analysis and prognosis in cancer patients: results from the clarify study M Torrente, PA Sousa, R Hernández, M Blanco, V Calvo, A Collazo, ... Cancers 14 (16), 4041, 2022 | 32 | 2022 |
| Using drug similarities for discovery of possible adverse reactions E Muñoz, V Nováček, PY Vandenbussche AMIA Annual Symposium Proceedings 2016, 924, 2017 | 30 | 2017 |
| Infrastructure for dynamic knowledge integration—Automated biomedical ontology extension using textual resources V Nováček, L Laera, S Handschuh, B Davis Journal of biomedical informatics 41 (5), 816-828, 2008 | 29 | 2008 |
| Semi-automatic integration of learned ontologies into a collaborative framework V Novácek, L Laera, S Handschuh International Workshop on Ontology Dynamics (IWOD-07), 13, 2007 | 29 | 2007 |
| Accurate prediction of kinase-substrate networks using knowledge graphs V Nováček, G McGauran, D Matallanas, A Vallejo Blanco, P Conca, ... PLoS computational biology 16 (12), e1007578, 2020 | 26 | 2020 |
| Empirical merging of ontologies—a proposal of universal uncertainty representation framework V Nováček, P Smrž European Semantic Web Conference, 65-79, 2006 | 23 | 2006 |
| Getting the meaning right: A complementary distributional layer for the web semantics V Nováček, S Handschuh, S Decker International Semantic Web Conference, 504-519, 2011 | 22 | 2011 |
| Machine learning–assisted recurrence prediction for patients with early-stage non–small-cell lung cancer A Janik, M Torrente, L Costabello, V Calvo, B Walsh, C Camps, ... JCO Clinical Cancer Informatics 7, e2200062, 2023 | 19 | 2023 |
| CORAAL-Dive into publications, bathe in the knowledge. V Novácek, T Groza, S Handschuh, S Decker J. Web Semant. 8 (2-3), 176-181, 2010 | 19 | 2010 |
| Link prediction using multi part embeddings SK Mohamed, V Nováček The Semantic Web: 16th International Conference, ESWC 2019, Portorož …, 2019 | 17 | 2019 |
| Extending Community Ontology Using Automatically Generated Suggestions. V Novácek, M Dabrowski, SR Kruk, S Handschuh FLAIRS, 290-296, 2007 | 16 | 2007 |
| CORAAL–Towards Deep Exploitation of Textual Resources in Life Sciences V Nováček, T Groza, S Handschuh Conference on Artificial Intelligence in Medicine in Europe, 206-215, 2009 | 14 | 2009 |
Sameh K. MohamedUniversity of GalwayПотвърден имейл адрес: insight-centre.org
