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Recommendations for the article CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy.
| Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
|---|---|---|---|---|---|---|
| visibility_off | Interpretable Machine Learning for Perturbation Biology | Bo Yuan, Ciyue Shen, Augustin Luna, Anil Korkut, D. Marks, John Ingraham, C. Sander | 2019-08-28 | bioRxiv | 6 | 153 |
| visibility_off | Abstract 2102: Interpretable machine learning for perturbation biology | Judy Shen, Bo Yuan, Augustin Luna, Anil Korkut, D. Marks, John Ingraham, C. Sander | 2020-08-13 | Clinical Research (Excluding Clinical Trials) | 0 | 153 |
| visibility_off | Interpretable predictions of cellular behavior | Ananya Rastogi | 2021-03-01 | Nature Computational Science | 0 | 3 |
| visibility_off | Perturbation Biology: Inferring Signaling Networks in Cellular Systems | Evan J. Molinelli, Anil Korkut, Weiqing Wang, Martin L. Miller, N. Gauthier, Xiaohong Jing, Poorvi Kaushik, Qin He, Gordon Mills, D. Solit, C. Pratilas, M. Weigt, A. Braunstein, A. Pagnani, R. Zecchina, C. Sander | 2013-08-23 | PLoS Computational Biology | 129 | 153 |
| visibility_off | A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations | Yunseong Kim, Y. Han, Corbin Hopper, Jonghoon Lee, J. Joo, Jeong-Ryeol Gong, Chun-Kyung Lee, Seong-Hoon Jang, Junsoo Kang, Taeyoung Kim, Kwang-Hyun Cho | 2024-05-01 | Cell Reports Methods | 0 | 6 |
| visibility_off | Perturbation biology links temporal protein changes to drug responses in a melanoma cell line | Elin Nyman, R. Stein, Xiaohong Jing, Weiqing Wang, Benjamin Marks, I. Zervantonakis, Anil Korkut, N. Gauthier, C. Sander | 2019-03-06 | PLoS Computational Biology | 12 | 153 |
| visibility_off | Causal Models, Prediction, and Extrapolation in Cell Line Perturbation Experiments | J. Long, Yumeng Yang, K. Do | 2022-07-20 | ArXiv | 0 | 63 |
| visibility_off | Interpretable Modeling of Single-cell perturbation Responses to Novel Drugs Using Cycle Consistence Learning | Wei Huang, Aichun Zhu, Hui Liu | 2023-11-17 | ArXiv | 0 | 0 |
| visibility_off | Predicting single-cell cellular responses to perturbations using cycle consistency learning. | Wei Huang, Hui Liu | 2024-06-28 | Bioinformatics | 0 | 0 |
| visibility_off | Predicting dynamic signaling network response under unseen perturbations | Fan Zhu, Y. Guan | 2014-10-01 | Bioinformatics | 15 | 38 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |