| Matchmaker: A deep learning framework for drug synergy prediction H brahim Kuru, O Tastan, E Cicek IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021 | 88 | 2021 |
| DeepSide: a deep learning approach for drug side effect prediction OC Uner, HI Kuru, RG Cinbis, O Tastan, AE Cicek IEEE/ACM Transactions on Computational Biology and Bioinformatics 20 (1 …, 2022 | 37* | 2022 |
| Graph embeddings on protein interaction networks Hİ Kuru PQDT-Global, 2019 | 1 | 2019 |
| From Cell-Lines to cancer patients: Personalized drug synergy prediction HI Kuru, AE Cicek, O Tastan Bioinformatics, btae134, 2024 | | 2024 |
| GEGE: predicting gene essentiality with graph embeddings Hİ Kuru, Yİ Tepeli, Ö Taştan Düzce Üniversitesi Bilim ve Teknoloji Dergisi 10 (3), 1567-1577, 2022 | | 2022 |
| PRER: A patient representation with pairwise relative expression of proteins on biological networks Hİ Kuru, M Buyukozkan, O Tastan PLoS Computational Biology 17 (5), e1008998, 2021 | | 2021 |
| Partially Ordered Expression Features Improves Survival Prediction in Cancer M Buyukozkan, HI Kuru, O Tastan | | |
