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Lineage Commitment01:21

Lineage Commitment

Commitment is the  process whereby stem cells:
Stem Cell Culture01:17

Stem Cell Culture

Stem cell research aims to find ways to use stem cells to regenerate and repair cellular damage. Over time, most adult cells undergo the wear and tear of aging and lose their ability to divide and repair themselves. Stem cells do not display a particular morphology or function. Adult stem cells, which exist as a small subset of cells in most tissues, keep dividing and can differentiate into a number of specialized cells generally formed by that tissue. These cells enable the body to renew and...
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Embryonic Stem Cells00:57

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Embryonic stem (ES) cells were first discovered in mice in 1981 by Martin Evans. In 1998, James Thomson identified a method to isolate embryonic stem cells from humans. Human embryonic stem cells (hESCs) are obtained from 3-5 day old embryos that remain unused after an in vitro fertilization procedure.
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Multipotency of Hematopoietic Stem Cells01:19

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Updated: Jun 23, 2026

Differentiation of a Human Neural Stem Cell Line on Three Dimensional Cultures, Analysis of MicroRNA and Putative Target Genes
10:48

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Published on: April 12, 2015

Stem cell decision making and critical-like exploratory networks.

Julianne D Halley1, Frank R Burden, David A Winkler

  • 1CSIRO Molecular and Health Technologies, Private Bag 10, Clayton South MDC 3169, Australia. julianne.halley@csiro.au

Stem Cell Research
|April 28, 2009
PubMed
Summary
This summary is machine-generated.

A new coarse-grained model explains stem cell fate decisions using self-organized criticality. This framework integrates intrinsic and extrinsic factors for better stem cell manipulation and therapeutic applications.

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Area of Science:

  • Systems Biology
  • Developmental Biology
  • Computational Biology

Background:

  • A lack of theoretical models for gene regulatory processes controlling stem cell fate hinders therapeutic applications.
  • Reductionist approaches using molecular components are insufficient for modeling complex stem cell regulatory and signaling pathways.

Purpose of the Study:

  • To present a coarse-grained, mesoscale model for stem cell decision-making.
  • To propose a conceptual framework integrating intrinsic and extrinsic factors governing stem cell fate.
  • To provide a pathway for developing predictive computational models of stem cell behavior.

Main Methods:

  • Utilizing the concept of self-organized criticality (SOC) in a coarse-grained model.
  • Modeling stochastic gene expression within stem cell gene regulatory networks.
  • Incorporating gene network connectivity and microenvironmental influences on cell fate decisions.

Main Results:

  • Stem cell gene regulatory networks self-organize to a critical-like state, priming diverse cell fate transcriptional programs.
  • Stem cell fate decisions involve increased gene network connectivity and transcription as cells leave their niche.
  • Competitive interactions between gene modules, influenced by microenvironment, occur as cell fates approach critical points.

Conclusions:

  • The proposed model offers a mesoscale perspective on stem cell fate regulation, moving beyond reductionist limitations.
  • The conceptual model integrates both internal stem cell dynamics and external microenvironmental cues.
  • Rapid self-organized criticality is suggested as a more fitting description for the mesoscale organization of gene regulatory networks.