ArticleCell proliferation2009
A novel view on stem cell development: analysing the shape of cellular genealogies.
Article in Cell proliferation, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- CellTrackVis: analyzing the performance of cell tracking algorithms.Eurographics/IEEE VGTC Symposium on Visualization : EUROVIS : [proceedings]. Eurographics/IEEE VGTC Symposium on Visualization · 2022Article
- Ontology patterns for the representation of quality changes of cells in time.Journal of biomedical semantics · 2019Article
- Estimation methods for heterogeneous cell population models in systems biology.Journal of the Royal Society, Interface · 2018Review
- Lineage marker synchrony in hematopoietic genealogies refutes the PU.1/GATA1 toggle switch paradigm.Nature communications · 2018Article
- Dissecting mechanisms of mouse embryonic stem cells heterogeneity through a model-based analysis of transcription factor dynamics.Journal of the Royal Society, Interface · 2016Article
- Quantitative semi-automated analysis of morphogenesis with single-cell resolution in complex embryos.Development (Cambridge, England) · 2012Article
- A novel validation algorithm allows for automated cell tracking and the extraction of biologically meaningful parameters.PloS one · 2011Article
- Designing materials to direct stem-cell fate.Nature · 2009Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe analysis of individual cell fates within a population of stem and progenitor cells is still a major experimental challenge in stem cell biology. However, new monitoring techniques, such as high-resolution time-lapse video microscopy, facilitate tracking and quantitative analysis of single cells and their progeny. Information on cellular development, divisional history and differentiation are naturally comprised into a pedigree-like structure, denoted as cellular genealogy. To extract reliable information concerning effecting variables and control mechanisms underlying cell fate decisions, it is necessary to analyse a large number of cellular genealogies. MATERIALS AND
methodsHere, we propose a set of statistical measures that are specifically tailored for the analysis of cellular genealogies. These measures address the degree and symmetry of cellular expansion, as well as occurrence and correlation of characteristic events such as cell death. Furthermore, we discuss two different methods for reconstruction of lineage fate decisions and show their impact on the interpretation of asymmetric developments. In order to illustrate these techniques, and to circumvent the present shortage of available experimental data, we obtain cellular genealogies from a single-cell-based mathematical model of haematopoietic stem cell organization. RESULTS AND
conclusionsBased on statistical analysis of cellular genealogies, we conclude that effects of external variables, such as growth conditions, are imprinted in their topology. Moreover, we demonstrate that it is essential to analyse timing of cell fate-specific changes and of occurrence of cell death events in the divisional context in order to understand the mechanisms of lineage commitment.
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