The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.
High-speed fluorescence image–enabled cell sorting
Open accessAbstract
Fast and selective isolation of single cells with unique spatial and morphological traits remains a technical challenge. Here, we address this by establishing high-speed image-enabled cell sorting (ICS), which records multicolor fluorescence images and sorts cells based on measurements from image data at speeds up to 15,000 events per second. We show that ICS quantifies cell morphology and localization of labeled proteins and increases the resolution of cell cycle analyses by separating mitotic stages. We combine ICS with CRISPR-pooled screens to identify regulators of the nuclear factor κB (NF-κB) pathway, enabling the completion of genome-wide image-based screens in about 9 hours of run time. By assessing complex cellular phenotypes, ICS substantially expands the phenotypic space accessible to cell-sorting applications and pooled genetic screening.
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Fiji: an open-source platform for biological-image analysis
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2019 · Cited by 66,890
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., et al. (2020) · Nature · doi:10.1038/s41586-020-2649-2 · Cited by 23,826
Harris, C., Millman, K., van der Walt, S., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N., et al. (2020) · RePEc: Research Papers in Economics · Cited by 17,844
Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1131 · Cited by 17,749
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2019) · Apollo - University of Cambridge Repository · doi:10.17863/cam.64134 · Cited by 10,460
Building Predictive Models in R Using the caret Package
Kuhn, M. (2008) · Journal of Statistical Software · doi:10.18637/jss.v028.i05 · Cited by 8,863
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
The Reactome pathway Knowledgebase
Fabregat, A., Sidiropoulos, K., Garapati, P., Gillespie, M., Hausmann, K., Haw, R., Jassal, B., Jupe, S., Korninger, F., McKay, S., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1351 · Cited by 5,605
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Funk, L., Su, K.-C., Ly, J., Feldman, D., Singh, A., Moodie, B., Blainey, P. C., & Cheeseman, I. M. (2022) · Cell · doi:10.1016/j.cell.2022.10.017 · Cited by 160
Rood, J. E., Hupalowska, A., & Regev, A. (2024) · Cell · doi:10.1016/j.cell.2024.07.035 · Cited by 139
Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence
Duran-Frigola, M., Cigler, M., & Winter, G. E. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.2c11098 · Cited by 50
Recent Developments (After 2020) in Flow Cytometry Worldwide and Within China
Du, X., Chen, X., Gao, C., Wang, J., Huo, X., & Chen, J. (2025) · Biosensors · doi:10.3390/bios15030156 · Cited by 10
Metadata
- Authors
- Schraivogel, D., Kuhn, T. M., Rauscher, B., Rodríguez-Martínez, M., Paulsen, M., Owsley, K., Middlebrook, A., Tischer, C., Ramasz, B., Ordoñez-Rueda, D., Dees, M., Cuylen-Haering, S., Diebold, E., & Steinmetz, L. M.
- Venue
- Science
- Published
- 2022-01-21
- Volume
- 375
- Issue
- 6578
- Pages
- 315-320
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W4206511670
- Cited by
- 284
- References
- 99
- FWCI
- 23.89
- Type
- journal article
- Language
- en
- Open access
- green
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- Schraivogel, D., Kuhn, T. M., Rauscher, B., Rodríguez-Martínez, M., Paulsen, M., Owsley, K., Middlebrook, A., Tischer, C., Ramasz, B., Ordoñez-Rueda, D., Dees, M., Cuylen-Haering, S., Diebold, E., & Steinmetz, L. M. (2022). High-speed fluorescence image–enabled cell sorting. Science. https://doi.org/10.1126/science.abj3013
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