Modeling gene networks to understand multistability in stem cells

David Menn, Xiao Wang

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Stem cells are unique in their ability to differentiate into diverse phenotypes capable of displaying radically different, yet stable, gene expression profiles. Understanding this multistable behavior is key to rationally influencing stem cell differentiation for both research and therapeutic purposes. To this end, mathematical paradigms have been adopted to simulate and explain the dynamics of complex gene networks. In this chapter, we introduce strategies for building deterministic and stochastic mathematical models of gene expression and demonstrate how analysis of these models can benefit our understanding of complex observed behaviors. Developing a mathematical understanding of biological processes is of utmost importance in understanding and controlling stem cell behavior.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages173-189
Number of pages17
DOIs
StatePublished - Jan 1 2019
Externally publishedYes

Publication series

NameMethods in Molecular Biology
Volume1975
ISSN (Print)1064-3745

Keywords

  • Differential equations
  • Modeling
  • Network topology
  • Parameterization
  • Stochasticity
  • Synthetic biology

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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  • Cite this

    Menn, D., & Wang, X. (2019). Modeling gene networks to understand multistability in stem cells. In Methods in Molecular Biology (pp. 173-189). (Methods in Molecular Biology; Vol. 1975). Humana Press Inc.. https://doi.org/10.1007/978-1-4939-9224-9_8