| Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning NF Greenwald, G Miller, E Moen, A Kong, A Kagel, T Dougherty, ... Nature biotechnology 40 (4), 555-565, 2022 | 516 | 2022 |
| DeepCell Kiosk: scaling deep learning–enabled cellular image analysis with Kubernetes D Bannon, E Moen, M Schwartz, E Borba, T Kudo, N Greenwald, ... Nature methods 18 (1), 43-45, 2021 | 116 | 2021 |
| Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning E Moen, E Borba, G Miller, M Schwartz, D Bannon, N Koe, I Camplisson, ... Biorxiv, 803205, 2019 | 62 | 2019 |
| A spatially resolved timeline of the human maternal–fetal interface S Greenbaum, I Averbukh, E Soon, G Rizzuto, A Baranski, NF Greenwald, ... Nature 619 (7970), 595-605, 2023 | 37 | 2023 |
| Dynamic allocation of computational resources for deep learning-enabled cellular image analysis with Kubernetes D Bannon, E Moen, M Schwartz, E Borba, S Cui, K Huang, I Camplisson, ... BioRxiv, 505032, 2018 | 12 | 2018 |
| A foundation model for cell segmentation U Israel, M Marks, R Dilip, Q Li, C Yu, E Laubscher, S Li, M Schwartz, ... bioRxiv, 2023 | 10 | 2023 |
| Spatiotemporal coordination at the maternal-fetal interface promotes trophoblast invasion and vascular remodeling in the first half of human pregnancy S Greenbaum, I Averbukh, E Soon, G Rizzuto, A Baranski, NF Greenwald, ... Biorxiv, 2021.09. 08.459490, 2021 | 9 | 2021 |
| Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. bioRxiv [Internet]. biorxiv. org; 2021 NF Greenwald, G Miller, E Moen, A Kong, A Kagel, CC Fullaway, ... CrossRef][PubMed], 2021 | 7 | 2021 |
| Characterizing the diverse cells that associate with the developing commissures of the zebrafish forebrain J Schnabl, MPH Litz, C Schneider, N PenkoffLidbeck, S Bashiruddin, ... Developmental Neurobiology 81 (5), 671-695, 2021 | 6 | 2021 |
| Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning. bioRxiv, 803205 E Moen, E Borba, G Miller, M Schwartz, D Bannon, N Koe, I Camplisson, ... | 6 | 2019 |
| Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning. bioRxiv E Moen, E Borba, G Miller, M Schwartz, D Bannon, N Koe, I Camplisson, ... oct, 2019 | 6 | 2019 |
| Scaling biological discovery at the interface of deep learning and cellular imaging M Schwartz, U Israel, X Wang, E Laubscher, C Yu, R Dilip, Q Li, J Mari, ... Nature Methods 20 (7), 956-957, 2023 | 3 | 2023 |
| Neurofibrillary tangle predominant dementia: clinical and pathological description in a case series M Schwartz, G Serrano, TG Beach, A Tsai, M Malek-Ahmadi, ... J Alzheimers Dis Parkinsonism 6 (204), 2161-0460.1000204, 2016 | 3 | 2016 |
| ΔSCOPE: A new method to quantify 3D biological structures and identify differences in zebrafish forebrain development MS Schwartz, J Schnabl, MPH Litz, BS Baumer, M Barresi Developmental biology 460 (2), 115-138, 2020 | 2 | 2020 |
| Accelerating Biological Discovery with Deep Learning and Spatial Optical Barcodes MS Schwartz California Institute of Technology, 2024 | | 2024 |
| Deep learning enabled spatial optical barcodes for pooled library screens MS Schwartz, DA Van Valen, E Pao US Patent App. 17/088,594, 2021 | | 2021 |
| DeepCell Foundry: Machine Learning Infrastructure for Single-Cell Biology EK Moen, MS Schwartz, G Miller, N Greenwald, T Dougherty, W Graf, ... | | |
David Van ValenCalifornia Institute of Technology在 caltech.edu 的电子邮件经过验证
