scholarly journals Single cell analysis of proliferation and movement of cancer and normal-like cells on nanowire array substrates

2018 ◽  
Vol 6 (43) ◽  
pp. 7042-7049 ◽  
Author(s):  
Zhen Li ◽  
Sofia Kamlund ◽  
Till Ryser ◽  
Mercy Lard ◽  
Stina Oredsson ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Nanowire Array ◽  
Nanowire Arrays ◽  
Cell Populations ◽  
Cell Analysis

Performing single cell analysis can reveal the existence of different cell populations on nanowire arrays.

scholarly journals Single-Cell Analysis of the Normal Mouse Aorta Reveals Functionally Distinct Endothelial Cell Populations

Circulation ◽  
2019 ◽  
Vol 140 (2) ◽  
pp. 147-163 ◽  
Author(s):  
Aditya S. Kalluri ◽  
Shamsudheen K. Vellarikkal ◽  
Elazer R. Edelman ◽  
Lan Nguyen ◽  
Ayshwarya Subramanian ◽  
...  
Keyword(s):  
Endothelial Cell ◽  
Single Cell ◽  
Normal Mouse ◽  
Single Cell Analysis ◽  
Cell Populations ◽  
Cell Analysis ◽  
Mouse Aorta

scholarly journals Multi-omic single cell analysis resolves novel stromal cell populations in healthy and diseased human tendon

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Adrian R. Kendal ◽  
Thomas Layton ◽  
Hussein Al-Mossawi ◽  
Louise Appleton ◽  
Stephanie Dakin ◽  
...  
Keyword(s):  
Single Cell ◽  
Stromal Cell ◽  
Single Cell Analysis ◽  
Cell Populations ◽  
Cell Analysis ◽  
Human Tendon

Large-scale arrays of picolitre chambers for single-cell analysis of large cell populations

Lab on a Chip ◽  
2010 ◽  
Vol 10 (21) ◽  
pp. 2952 ◽  
Author(s):  
Won Chul Lee ◽  
Sara Rigante ◽  
Albert P. Pisano ◽  
Frans A. Kuypers
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Single Cell Analysis ◽  
Large Cell ◽  
Cell Populations ◽  
Cell Analysis

scholarly journals Single-Cell Analysis of Placenta Accreta Spectrum Reveals Functionally Distinct Cell Populations

2022 ◽  
Vol 226 (1) ◽  
pp. S737
Author(s):  
Ophelia Yin ◽  
Deanna Wong ◽  
Feiyang Ma ◽  
Christine Jang ◽  
Anhyo Jeong ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Placenta Accreta ◽  
Cell Populations ◽  
Cell Analysis ◽  
Distinct Cell ◽  
Placenta Accreta Spectrum

scholarly journals FastPG: Fast clustering of millions of single cells

2020 ◽  
Author(s):  
Tom Bodenheimer ◽  
Mahantesh Halappanavar ◽  
Stuart Jefferys ◽  
Ryan Gibson ◽  
Siyao Liu ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Computation Time ◽  
Unsupervised Clustering ◽  
Cell Populations ◽  
Cell Analysis ◽  
Clustering Methods ◽  
Assignment Accuracy ◽  
Cell Assignment

AbstractCurrent single-cell experiments can produce datasets with millions of cells. Unsupervised clustering can be used to identify cell populations in single-cell analysis but often leads to interminable computation time at this scale. This problem has previously been mitigated by subsampling cells, which greatly reduces accuracy. We built on the graph-based algorithm PhenoGraph and developed FastPG which has the same cell assignment accuracy but is on average 27x faster in our tests. FastPG also has higher cell assignment accuracy than two other fast clustering methods, FlowSOM and PARC.AvailabilityFastPG is available here: https://github.com/sararselitsky/FastPG

scholarly journals Image3C: a multimodal image-based and label independent integrative method for single-cell analysis

2019 ◽  
Author(s):  
Alice Accorsi ◽  
Andrew C. Box ◽  
Robert Peuß ◽  
Christopher Wood ◽  
Alejandro Sánchez Alvarado ◽  
...  
Keyword(s):  
Neural Network ◽  
Single Cell ◽  
Single Cell Analysis ◽  
De Novo ◽  
Image Cytometry ◽  
Cell Populations ◽  
Composition Analysis ◽  
Cell Analysis ◽  
Cell Classification ◽  
Species Specific

AbstractImage-based cell classification has become a common tool to identify phenotypic changes in cell populations. However, this methodology is limited to organisms possessing well characterized species-specific reagents (e.g., antibodies) that allow cell identification, clustering and convolutional neural network (CNN) training. In the absence of such reagents, the power of image-based classification has remained mostly off-limits to many research organisms. We have developed an image-based classification methodology we named Image3C (Image-Cytometry Cell Classification) that does not require species-specific reagents nor pre-existing knowledge about the sample. Image3C combines image-based flow cytometry with an unbiased, high-throughput cell cluster pipeline and CNN integration. Image3C exploits intrinsic cellular features and non-species-specific dyes to perform de novo cell composition analysis and to detect changes in cellular composition between different conditions. Therefore, Image3C expands the use of imaged-based analyses of cell population composition to research organisms in which detailed cellular phenotypes are unknown or for which species-specific reagents are not available.Impact statementImage3C analyzes cell populations through image-based clustering and neural network training, which allows single-cell analysis in research organisms devoid of species-specific reagents or pre-existing knowledge on cell phenotypes.

scholarly journals Single Cell Analysis of Complex Thymus Stromal Cell Populations: Rapid Thymic Epithelia Preparation Characterizes Radiation Injury

2009 ◽  
Vol 2 (4) ◽  
pp. 279-285 ◽  
Author(s):  
Kirsten M. Williams ◽  
Heather Mella ◽  
Philip J. Lucas ◽  
Joy A. Williams ◽  
William Telford ◽  
...  
Keyword(s):  
Single Cell ◽  
Stromal Cell ◽  
Radiation Injury ◽  
Single Cell Analysis ◽  
Cell Populations ◽  
Cell Analysis
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