| Uncovering cancer gene regulation by accurate regulatory network inference from uninformative data D Seçilmiş, T Hillerton, D Morgan, A Tjärnberg, S Nelander, TEM Nordling, ... NPJ systems biology and applications 6 (1), 1-8, 2020 | 17 | 2020 |
| Fast and accurate gene regulatory network inference by normalized least squares regression T Hillerton, D Seçilmiş, S Nelander, ELL Sonnhammer Bioinformatics 38 (8), 2263-2268, 2022 | 10 | 2022 |
| GRNbenchmark-a web server for benchmarking directed gene regulatory network inference methods D Seçilmiş, T Hillerton, ELL Sonnhammer Nucleic Acids Research, 2022 | 7 | 2022 |
| Knowledge of the perturbation design is essential for accurate gene regulatory network inference D Seçilmiş, T Hillerton, A Tjärnberg, S Nelander, TEM Nordling, ... Scientific reports 12 (1), 1-12, 2022 | 6 | 2022 |
| Inferring the experimental design for accurate gene regulatory network inference D Seçilmiş, T Hillerton, S Nelander, ELL Sonnhammer Bioinformatics 37 (20), 3553-3559, 2021 | 5 | 2021 |
| Two New Nonparametric Models for Biological Networks D Seçilmiş, M Ağraz, V Purutçuoğlu Bayesian Reasoning and Gaussian Processes for Machine Learning Applications …, 2022 | 3 | 2022 |
| Optimal sparsity selection based on information criteria for accurate gene regulatory network inference D Seçilmiş, S Nelander, E Sonnhammer | 2 | 2021 |
| Deterministic modeling and inference of biological systems D Seçilmiş Middle East Technical University, 2017 | 2 | 2017 |
| Modeling of Biochemical Networks via Classification and Regression Tree Methods D Seçilmiş, V Purutçuoğlu Mathematical Methods in Engineering, 87-102, 2019 | 1 | 2019 |
| Improving the accuracy of gene regulatory network inference from noisy data D Seçilmiş Department of Biochemistry and Biophysics, Stockholm University, 2021 | | 2021 |
| Karmaşık biyolojk sistemlerin deterministik modellemelerinde alternatif yaklaşımlar, parametre tahmini ve kopulalar V Purutçuoğlu Gazi, T Şeker, GW Weber, E Purutçuoğlu, E Ayyildiz, T Akal, ... | | 2016 |
