Intelligent image-based in situ single-cell isolation
Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of captur...
Elmentve itt :
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| Dokumentumtípus: | Cikk |
| Megjelent: |
2018
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| Sorozat: | NATURE COMMUNICATIONS
9 No. 1 |
| doi: | 10.1038/s41467-017-02628-4 |
| mtmt: | 3318793 |
| Online Access: | http://publicatio.bibl.u-szeged.hu/17905 |
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| 490 | 0 | |a NATURE COMMUNICATIONS |v 9 No. 1 | |
| 520 | 3 | |a Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample. | |
| 700 | 0 | 1 | |a Smith Kevin |e aut |
| 700 | 0 | 1 | |a Molnár Csaba |e aut |
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| 700 | 0 | 1 | |a Döme Lili |e aut |
| 700 | 0 | 1 | |a Bálind Árpád |e aut |
| 700 | 0 | 1 | |a Balassa Tamás |e aut |
| 700 | 0 | 1 | |a Szkalisity Ábel |e aut |
| 700 | 0 | 1 | |a Kocsis Ágnes Katalin |e aut |
| 700 | 0 | 1 | |a Bálint Balázs |e aut |
| 700 | 0 | 1 | |a Enyedi Márton Zsolt |e aut |
| 700 | 0 | 1 | |a Nagy István |e aut |
| 700 | 0 | 1 | |a Puskás László |e aut |
| 700 | 0 | 1 | |a Haracska Lajos |e aut |
| 700 | 0 | 1 | |a Tamás Gábor |e aut |
| 700 | 0 | 1 | |a Horváth Péter |e aut |
| 856 | 4 | 0 | |u http://publicatio.bibl.u-szeged.hu/17905/1/s41467-017-02628-4.pdf |z Dokumentum-elérés |