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Journal article
Computational Image Analysis Reveals Intrinsic Multigenerational Differences between Anterior and Posterior Cerebral Cortex Neural Progenitor Cells
Stem cell reports, v 5(4), pp 609-620
13 Oct 2015
PMID: 26344906
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Time-lapse microscopy can capture patterns of development through multiple divisions for an entire clone of proliferating cells. Images are taken every few minutes over many days, generating data too vast to process completely by hand. Computational analysis of this data can benefit from occasional human guidance. Here we combine improved automated algorithms with minimized human validation to produce fully corrected segmentation, tracking, and lineaging results with dramatic reduction in effort. A web-based viewer provides access to data and results. The improved approach allows efficient analysis of large numbers of clones. Using this method, we studied populations of progenitor cells derived from the anterior and posterior embryonic mouse cerebral cortex, each growing in a standardized culture environment. Progenitors from the anterior cortex were smaller, less motile, and produced smaller clones compared to those from the posterior cortex, demonstrating cell-intrinsic differences that may contribute to the areal organization of the cerebral cortex.
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Details
- Title
- Computational Image Analysis Reveals Intrinsic Multigenerational Differences between Anterior and Posterior Cerebral Cortex Neural Progenitor Cells
- Creators
- Mark R Winter - Drexel UniversityMo Liu - Neural Stem Cell InstituteDavid Monteleone - Drexel UniversityJustin Melunis - Drexel UniversityUri Hershberg - Drexel UniversitySusan K Goderie - Neural Stem Cell InstituteSally Temple - Neural Stem Cell InstituteAndrew R Cohen - Drexel University
- Publication Details
- Stem cell reports, v 5(4), pp 609-620
- Publisher
- Elsevier
- Grant note
- R01NS076709 / NINDS NIH HHS R01 AG041861 / NIA NIH HHS R01 NS076709 / NINDS NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000364990900014
- Scopus ID
- 2-s2.0-84944442050
- Other Identifier
- 991019167547304721
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Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Cell & Tissue Engineering
- Cell Biology