Intelligent image-based in situ single-cell isolation

The isolation of single cells while retaining context is important for quantifying cellular heterogeneity but technically challenging. Here, the authors develop a high-throughput, scalable workflow for microscopy-based single cell isolation using machine-learning, high-throughput microscopy and lase...

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Autores principales:	Csilla Brasko, Kevin Smith, Csaba Molnar, Nora Farago, Lili Hegedus, Arpad Balind, Tamas Balassa, Abel Szkalisity, Farkas Sukosd, Katalin Kocsis, Balazs Balint, Lassi Paavolainen, Marton Z. Enyedi, Istvan Nagy, Laszlo G. Puskas, Lajos Haracska, Gabor Tamas, Peter Horvath
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/45fa759495a24fc3831e7ab0ebc0ea21
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spelling	oai:doaj.org-article:45fa759495a24fc3831e7ab0ebc0ea212021-12-02T17:31:45ZIntelligent image-based in situ single-cell isolation10.1038/s41467-017-02628-42041-1723https://doaj.org/article/45fa759495a24fc3831e7ab0ebc0ea212018-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-02628-4https://doaj.org/toc/2041-1723The isolation of single cells while retaining context is important for quantifying cellular heterogeneity but technically challenging. Here, the authors develop a high-throughput, scalable workflow for microscopy-based single cell isolation using machine-learning, high-throughput microscopy and laser capture microdissection.Csilla BraskoKevin SmithCsaba MolnarNora FaragoLili HegedusArpad BalindTamas BalassaAbel SzkalisityFarkas SukosdKatalin KocsisBalazs BalintLassi PaavolainenMarton Z. EnyediIstvan NagyLaszlo G. PuskasLajos HaracskaGabor TamasPeter HorvathNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-7 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Csilla Brasko Kevin Smith Csaba Molnar Nora Farago Lili Hegedus Arpad Balind Tamas Balassa Abel Szkalisity Farkas Sukosd Katalin Kocsis Balazs Balint Lassi Paavolainen Marton Z. Enyedi Istvan Nagy Laszlo G. Puskas Lajos Haracska Gabor Tamas Peter Horvath Intelligent image-based in situ single-cell isolation
description	The isolation of single cells while retaining context is important for quantifying cellular heterogeneity but technically challenging. Here, the authors develop a high-throughput, scalable workflow for microscopy-based single cell isolation using machine-learning, high-throughput microscopy and laser capture microdissection.
format	article
author	Csilla Brasko Kevin Smith Csaba Molnar Nora Farago Lili Hegedus Arpad Balind Tamas Balassa Abel Szkalisity Farkas Sukosd Katalin Kocsis Balazs Balint Lassi Paavolainen Marton Z. Enyedi Istvan Nagy Laszlo G. Puskas Lajos Haracska Gabor Tamas Peter Horvath
author_facet	Csilla Brasko Kevin Smith Csaba Molnar Nora Farago Lili Hegedus Arpad Balind Tamas Balassa Abel Szkalisity Farkas Sukosd Katalin Kocsis Balazs Balint Lassi Paavolainen Marton Z. Enyedi Istvan Nagy Laszlo G. Puskas Lajos Haracska Gabor Tamas Peter Horvath
author_sort	Csilla Brasko
title	Intelligent image-based in situ single-cell isolation
title_short	Intelligent image-based in situ single-cell isolation
title_full	Intelligent image-based in situ single-cell isolation
title_fullStr	Intelligent image-based in situ single-cell isolation
title_full_unstemmed	Intelligent image-based in situ single-cell isolation
title_sort	intelligent image-based in situ single-cell isolation
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/45fa759495a24fc3831e7ab0ebc0ea21
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Intelligent image-based in situ single-cell isolation

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