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 | 86 | 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 bioRxiv, 2023.02. 13.528276, 2023 | | 2023 |
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 | | |