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A Comprehensive Model of the Spatio-Temporal Stem Cell and Tissue Organisation in the Intestinal Crypt

Overview of attention for article published in PLoS Computational Biology, January 2011
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Title
A Comprehensive Model of the Spatio-Temporal Stem Cell and Tissue Organisation in the Intestinal Crypt
Published in
PLoS Computational Biology, January 2011
DOI 10.1371/journal.pcbi.1001045
Pubmed ID
Authors

Peter Buske, Jörg Galle, Nick Barker, Gabriela Aust, Hans Clevers, Markus Loeffler

Abstract

We introduce a novel dynamic model of stem cell and tissue organisation in murine intestinal crypts. Integrating the molecular, cellular and tissue level of description, this model links a broad spectrum of experimental observations encompassing spatially confined cell proliferation, directed cell migration, multiple cell lineage decisions and clonal competition.Using computational simulations we demonstrate that the model is capable of quantitatively describing and predicting the dynamic behaviour of the intestinal tissue during steady state as well as after cell damage and following selective gain or loss of gene function manipulations affecting Wnt- and Notch-signalling. Our simulation results suggest that reversibility and flexibility of cellular decisions are key elements of robust tissue organisation of the intestine. We predict that the tissue should be able to fully recover after complete elimination of cellular subpopulations including subpopulations deemed to be functional stem cells. This challenges current views of tissue stem cell organisation.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 268 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
United Kingdom 3 1%
Chile 1 <1%
France 1 <1%
Portugal 1 <1%
Germany 1 <1%
South Africa 1 <1%
Brazil 1 <1%
Australia 1 <1%
Other 4 1%
Unknown 251 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 78 29%
Researcher 60 22%
Student > Master 37 14%
Student > Bachelor 19 7%
Professor > Associate Professor 12 4%
Other 37 14%
Unknown 25 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 99 37%
Biochemistry, Genetics and Molecular Biology 38 14%
Medicine and Dentistry 20 7%
Engineering 20 7%
Physics and Astronomy 19 7%
Other 40 15%
Unknown 32 12%