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Recommendations for the article Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade
| Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
|---|---|---|---|---|---|---|
| visibility_off | Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade | M. Przedborski, Munisha Smalley, S. Thiyagarajan, A. Goldman, M. Kohandel | 2021-07-15 | Communications Biology | 9 | 28 |
| visibility_off | Integrating Systems Biology and an Ex Vivo Human Tumor Model Elucidates PD-1 Blockade Response Dynamics | Munisha Smalley, Munisha Smalley, M. Przedborski, S. Thiyagarajan, Moriah Pellowe, A. Verma, N. Brijwani, Debika Datta, Misti Jain, Basavaraja U. Shanthappa, Vidushi Kapoor, K. Gopinath, D. C. Doval, K. Sabitha, G. Taroncher-Oldenburg, B. Majumder, P. Majumder, M. Kohandel, Aaron Goldman, Aaron Goldman | 2020-06-01 | iScience | 6 | 73 |
| visibility_off | Network-based machine learning approach to predict immunotherapy response in cancer patients | JungHo Kong, Doyeon Ha, Juhun Lee, Inhae Kim, Minhyuk Park, S. Im, Kunyoo Shin, Sanguk Kim | 2022-06-28 | Nature Communications | 63 | 45 |
| visibility_off | Use of a systems-biology informed machine learning model to predict drug response using clinically available NGS data. | Maayan Baron, Andrey Chursov, Brandon Funkhouser, Jacob Kaffey, S. Sushanth Kumar, G. Komatsoulis, Felicia Kuperwaser, M. Ramchandran, J. Sherman, E. Vucic | 2023-06-01 | Journal of Clinical Oncology | 0 | 35 |
| visibility_off | Predictive systems biomarkers of response to immune checkpoint inhibitors | Óscar Lapuente-Santana, Maisa van Genderen, P. Hilbers, F. Finotello, Federica Eduati | 2021-02-07 | bioRxiv | 0 | 35 |
| visibility_off | A Computational Model of Neoadjuvant PD-1 Inhibition in Non-Small Cell Lung Cancer | M. Jafarnejad, Chang Gong, E. Gabrielson, I. Bartelink, P. Vicini, B. Wang, R. Narwal, L. Roskos, A. Popel | 2019-06-24 | The AAPS Journal | 49 | 69 |
| visibility_off | Hybridizing mechanistic mathematical modeling with deep learning methods to predict individual cancer patient survival after immune checkpoint inhibitor therapy | J. D. Butner, P. Dogra, Caroline Chung, Eugene J Koay, James Welsh, David Hong, Vittorio Cristini, Zhihui Wang | 2024-03-29 | Research Square | 0 | 16 |
| visibility_off | Biology-aware mutation-based deep learning for outcome prediction of cancer immunotherapy with immune checkpoint inhibitors | Junyan Liu, Md Tauhidul Islam, Shengtian Sang, Liang Qiu, Lei Xing | 2023-11-06 | NPJ Precision Oncology | 0 | 16 |
| visibility_off | Interpretable predictions of cellular behavior | Ananya Rastogi | 2021-03-01 | Nature Computational Science | 0 | 3 |
| visibility_off | Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology | Theinmozhi Arulraj, Hanwen Wang, Alberto Ippolito, Shuming Zhang, E. Fertig, Aleksander S. Popel | 2024-03-27 | Briefings in Bioinformatics | 0 | 43 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |