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Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
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Dataset for: Phenotyping single-cell motility in microfluidic confinement

Research datakeyboard_double_arrow_right Dataset 17 Oct 2022Publisher:ZenodoFunded by:EC | EvoMotion
Authors: Bentley, Samuel A.; Laeverenz-Schlogelhofer, Hannah; Anagnostidis, Vasileios; Cammann, Jan; Mazza, Marco G.; Gielen, Fabrice; Wan, Kirsty Y.;

doi: 10.5281/zenodo.7217571 , 10.5281/zenodo.7226288 , 10.5281/zenodo.7217572

Dataset for: Phenotyping single-cell motility in microfluidic confinement

Abstract

Additional funding sources Academy of Medical Sciences (The Academy of Medical Sciences): Kirsty Y Wan SBF003\1160 Biotechnology and Biological Sciences Research Council (BBSRC) : Fabrice Gielen BB/T011777/1 Engineering and Physical Sciences Research Council (EPSRC): Marco Mazza EP/T022108/1

Associated dataset and simulation codes for the publication "Phenotyping single-cell motility in microfluidic confinement" (2022), by Samuel A. Bentley, Hannah Laeverenz-Schlogelhofer, Vasileios Anagnostidis, Jan Cammann, Marco G. Mazza, Fabrice Gielen, Kirsty Y. Wan.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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