| A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia SI Lee*, S Celik*, BA Logsdon, SM Lundberg, TJ Martins, VG Oehler, ... Nature Communications 9 (42), 2018 | 333 | 2018 |
| Explainable machine learning prediction of synergistic drug combinations for precision cancer medicine JD Janizek, S Celik, SI Lee BioRxiv, 331769, 2018 | 50 | 2018 |
| DeepProfile: Deep learning of cancer molecular profiles for precision medicine AB Dincer, S Celik, N Hiranuma, SI Lee bioRxiv, 278739, 2018 | 49 | 2018 |
| Efficient dimensionality reduction for high-dimensional network estimation S Celik, B Logsdon, SI Lee International conference on machine learning, 1953-1961, 2014 | 38 | 2014 |
| Extracting a low-dimensional description of multiple gene expression datasets reveals a potential driver for tumor-associated stroma in ovarian cancer S Celik, BA Logsdon, S Battle, CW Drescher, M Rendi, RD Hawkins, ... Genome medicine 8, 1-31, 2016 | 24 | 2016 |
| Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer’s disease neuropathologies N Beebe-Wang, S Celik, E Weinberger, P Sturmfels, PL De Jager, ... Nature Communications 12 (1), 5369, 2021 | 17 | 2021 |
| Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models JD Janizek, AB Dincer, S Celik, H Chen, W Chen, K Naxerova, SI Lee Nature biomedical engineering 7 (6), 811-829, 2023 | 16 | 2023 |
| Biological cartography: Building and benchmarking representations of life S Celik, JC Hütter, SM Carlos, NH Lazar, R Mohan, C Tillinghast, ... Biorxiv, 2022.12. 09.519400, 2022 | 11 | 2022 |
| Rxrx3: Phenomics map of biology MM Fay, O Kraus, M Victors, L Arumugam, K Vuggumudi, J Urbanik, ... Biorxiv, 2023.02. 07.527350, 2023 | 9 | 2023 |
| DeepProfile: deep learning of cancer molecular profiles for precision medicine. bioRxiv: 278739 AB Dincer, S Celik, N Hiranuma, SI Lee | 9 | 2018 |
| Masked autoencoders are scalable learners of cellular morphology O Kraus, K Kenyon-Dean, S Saberian, M Fallah, P McLean, J Leung, ... arXiv preprint arXiv:2309.16064, 2023 | 7 | 2023 |
| PAUSE: principled feature attribution for unsupervised gene expression analysis JD Janizek, A Spiro, S Celik, BW Blue, JC Russell, TI Lee, M Kaeberlin, ... Genome Biology 24 (1), 81, 2023 | 7 | 2023 |
| Rxrx3: Phenomics map of biology. bioRxiv MM Fay, O Kraus, M Victors, L Arumugam, K Vuggumudi, J Urbanik, ... | 7 | 2023 |
| Contributions from the 2018 literature on bioinformatics and translational informatics M Smaïl-Tabbone, B Rance Yearbook of Medical Informatics 28 (01), 190-193, 2019 | 7 | 2019 |
| High-resolution genome-wide mapping of chromosome-arm-scale truncations induced by CRISPR–Cas9 editing NH Lazar, S Celik, L Chen, MM Fay, JC Irish, J Jensen, CA Tillinghast, ... Nature Genetics, 1-12, 2024 | 6 | 2024 |
| High throughput drug screening of leukemia stem cells reveals resistance to standard therapies and sensitivity to other agents in acute myeloid leukemia FL Mabrey, SS Chien, TS Martins, J Annis, TS Sekizaki, J Dai, ... Blood 132, 180, 2018 | 6 | 2018 |
| A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia. Nat. Commun, 9, 42 SI Lee, S Celik, BA Logsdon, SM Lundberg, TJ Martins, VG Oehler, ... | 6 | 2018 |
| A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia. Nat Commun. 2018; 9: 42 SI Lee, S Celik, BA Logsdon, SM Lundberg, TJ Martins, VG Oehler, ... | 6 | |
| Uncovering expression signatures of synergistic drug response using an ensemble of explainable AI models JD Janizek, AB Dincer, S Celik, H Chen, W Chen, K Naxerova, SI Lee BioRxiv, 2021.10. 06.463409, 2021 | 5 | 2021 |
| & Becker, PS (2018) SI Lee, S Celik, BA Logsdon, SM Lundberg, TJ Martins, VG Oehler, ... A machine learning approach to integrate big data for precision medicine in …, 0 | 5 | |
Su-In LeeComputer Science & Engineering, University of Washington在 cs.washington.edu 的电子邮件经过验证
