Literature DB >> 15486930

Cell population dynamics model for deconvolution of murine embryonic stem cell self-renewal and differentiation responses to cytokines and extracellular matrix.

Wendy A Prudhomme1, Keith H Duggar, Douglas A Lauffenburger.   

Abstract

Stem cell self-renewal versus differentiation fate decisions are difficult to characterize and analyze due to multiple competing rate processes occurring simultaneously among heterogeneous cell subpopulations. To address this challenge, we describe a mathematical model for cell population dynamics that allows flow cytometry measurement of population distributions of molecular markers to be deconvoluted in terms of subpopulation-specific rate parameters distinguishing commitment to differentiation, proliferation of differentiated cells, and proliferation of undifferentiated cells (i.e., self-renewal). We validate this model-based parameter determination by means of dedicated, independent cell-tracking studies. Our approach facilitates interpretation of relationships underlying effects of external cues on cell responses in differentiating cultures via intracellular signals. Copyright 2004 Wiley Periodicals, Inc.

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Year:  2004        PMID: 15486930     DOI: 10.1002/bit.20244

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  3 in total

1.  Kinetic analysis of neurotrophin-3-mediated differentiation of embryonic stem cells into neurons.

Authors:  Stephanie M Willerth; Shelly E Sakiyama-Elbert
Journal:  Tissue Eng Part A       Date:  2009-02       Impact factor: 3.845

2.  Improving efficiency of human pluripotent stem cell differentiation platforms using an integrated experimental and computational approach.

Authors:  Joshua A Selekman; Amritava Das; Nicholas J Grundl; Sean P Palecek
Journal:  Biotechnol Bioeng       Date:  2013-07-09       Impact factor: 4.530

3.  Reconstruction of cell population dynamics using CFSE.

Authors:  Andrew Yates; Cliburn Chan; Jessica Strid; Simon Moon; Robin Callard; Andrew J T George; Jaroslav Stark
Journal:  BMC Bioinformatics       Date:  2007-06-12       Impact factor: 3.169

  3 in total

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