Title |
Visualization and correction of automated segmentation, tracking and lineaging from 5-D stem cell image sequences
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Published in |
BMC Bioinformatics, October 2014
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DOI | 10.1186/1471-2105-15-328 |
Pubmed ID | |
Authors |
Eric Wait, Mark Winter, Chris Bjornsson, Erzsebet Kokovay, Yue Wang, Susan Goderie, Sally Temple, Andrew R Cohen |
Abstract |
Neural stem cells are motile and proliferative cells that undergo mitosis, dividing to produce daughter cells and ultimately generating differentiated neurons and glia. Understanding the mechanisms controlling neural stem cell proliferation and differentiation will play a key role in the emerging fields of regenerative medicine and cancer therapeutics. Stem cell studies in vitro from 2-D image data are well established. Visualizing and analyzing large three dimensional images of intact tissue is a challenging task. It becomes more difficult as the dimensionality of the image data increases to include time and additional fluorescence channels. There is a pressing need for 5-D image analysis and visualization tools to study cellular dynamics in the intact niche and to quantify the role that environmental factors play in determining cell fate. |
X Demographics
Geographical breakdown
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Canada | 1 | 17% |
United States | 1 | 17% |
United Kingdom | 1 | 17% |
Unknown | 3 | 50% |
Demographic breakdown
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Scientists | 2 | 33% |
Mendeley readers
Geographical breakdown
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Netherlands | 1 | 2% |
Australia | 1 | 2% |
Switzerland | 1 | 2% |
Unknown | 59 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 16 | 26% |
Researcher | 13 | 21% |
Student > Master | 7 | 11% |
Other | 5 | 8% |
Student > Doctoral Student | 3 | 5% |
Other | 11 | 18% |
Unknown | 7 | 11% |
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Arts and Humanities | 2 | 3% |
Other | 8 | 13% |
Unknown | 12 | 19% |