| Neuro-symbolic representation learning on biological knowledge graphs M Alshahrani, MA Khan, O Maddouri, AR Kinjo, N Queralt-Rosinach, ... Bioinformatics 33 (17), 2723-2730, 2017 | 166 | 2017 |
| Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes M Alshahrani, R Hoehndorf Bioinformatics 34 (17), i901-i907, 2018 | 68 | 2018 |
| The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants R Hoehndorf, M Alshahrani, GV Gkoutos, G Gosline, Q Groom, T Hamann, ... Journal of Biomedical Semantics 7 (1), 1-11, 2016 | 48 | 2016 |
| Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning MA Thafar, M Alshahrani, S Albaradei, T Gojobori, M Essack, X Gao Scientific reports 12 (1), 4751, 2022 | 39 | 2022 |
| Application and evaluation of knowledge graph embeddings in biomedical data M Alshahrani, MA Thafar, M Essack PeerJ Computer Science 7, e341, 2021 | 33 | 2021 |
| Hybrid Techniques for Diagnosis with WSIs for Early Detection of Cervical Cancer Based on Fusion Features BA Mohammed, EM Senan, ZG Al-Mekhlafi, M Alazmi, AM Alayba, ... Applied Sciences 12 (17), 8836, 2022 | 17 | 2022 |
| DANNP: an efficient artificial neural network pruning tool M Alshahrani, O Soufan, A Magana-Mora, VB Bajic PeerJ Computer Science 3, e137, 2017 | 16 | 2017 |
| Drug repurposing through joint learning on knowledge graphs and literature M Alshahrani, R Hoehndorf Biorxiv, 385617, 2018 | 12 | 2018 |
| Diagnosis of Histopathological Images to Distinguish Types of Malignant Lymphomas Using Hybrid Techniques Based on Fusion Features ZG Al-Mekhlafi, EM Senan, BA Mohammed, M Alazmi, AM Alayba, ... Electronics 11 (18), 2865, 2022 | 10 | 2022 |
| Combining biomedical knowledge graphs and text to improve predictions for drug-target interactions and drug-indications M Alshahrani, A Almansour, A Alkhaldi, MA Thafar, M Uludag, M Essack, ... PeerJ 10, e13061, 2022 | 9 | 2022 |
| OncoRTT: Predicting novel oncology-related therapeutic targets using BERT embeddings and omics features MA Thafar, S Albaradei, M Uludag, M Alshahrani, T Gojobori, M Essack, ... Frontiers in Genetics 14, 1139626, 2023 | 5 | 2023 |
| Knowledge Graph Representation Learning: Approaches and Applications in Biomedicine M AlShahrani | 2 | 2019 |
| Semantic Disease Gene M AlShahrani, R Hoehndorf Bioinformatics, 2018 | 1 | 2018 |
| SPARQL2OWL: Towards Bridging the Semantic Gap Between RDF and OWL. M Alshahrani, H Almashouq, R Hoehndorf ICBO/BioCreative, 2016 | 1 | 2016 |
| MahaThafar/Affinity2Vec: Drug-target binding affinity prediction using representation learning, graph mining, and machine learning MA Thafar, M Alshahrani, S Albaradei, T Gojobori, M Essack, X Gao Github, 2021 | | 2021 |
| bio-ontology-research-group/multi-drug-embedding: Method for drug repurposing from knowledge graphs and literature M AlShahrani, R Hoehndorf Github, 2018 | | 2018 |
| bio-ontology-research-group/SMUDGE: SmuDGE: Semantic Disease Gene Embeddings M AlShahrani, R Hoehndorf Github, 2017 | | 2017 |
| Additional file 1 of The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants R Hoehndorf, M Alshahrani, G Gkoutos, G Gosline, Q Groom, T Hamann, ... | | 2016 |
| bio-ontology-research-group/walking-rdf-and-owl: Feature learning over RDF data and OWL ontologies M AlShahrani, O Maddouri, AR Kinjo, N Queralt-Rosinach, R Hoehndorf, ... Github, 2016 | | 2016 |
| Supplementary Material for: The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants R Hoehndorf, M Alshahrani, G Gkoutos, G Gosline, Q Groom, T Hamann, ... Figshare, 2016 | | 2016 |
Robert HoehndorfKing Abdullah University of Science and TechnologyEmail được xác minh tại kaust.edu.sa
