Construction of a system using a deep learning algorithm to count cell numbers in nanoliter wells for viable single-cell experiments-Reference-Cited by-同舟云学术

Construction of a system using a deep learning algorithm to count cell numbers in nanoliter wells for viable single-cell experiments

Published:2017-12 Issue:1 Volume:7 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Kamatani Takashi,Fukunaga Koichi,Miyata Kaede,Shirasaki Yoshitaka,Tanaka Junji,Baba Rie,Matsusaka Masako,Kamatani Naoyuki,Moro Kazuyo,Betsuyaku Tomoko,Uemura Sotaro

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://www.nature.com/articles/s41598-017-17012-x.pdf

Reference18 articles.

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2. Jaitin, D. A. et al. Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq. Cell. 167, 1883–1896 (2016).

3. Olsson, A. et al. Single-cell analysis of mixed-lineage states leading to a binary cell fate choice. Nature. 537, 698–702 (2016).

4. Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science. 352, 189–96 (2016).

5. Shirasaki et al. Toward an understanding of immune cell sociology: real-time monitoring of cytokine secretion at the single-cell level. IUBMB Life. 65, 28–34 (2013).

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