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A geometrical perspective on development.

Archishman RajuEric D Siggia
Published in: Development, growth & differentiation (2023)
Cell fate decisions emerge as a consequence of a complex set of gene regulatory networks. Models of these networks are known to have more parameters than data can determine. Recent work, inspired by Waddington's metaphor of a landscape, has instead tried to understand the geometry of gene regulatory networks. Here, we describe recent results on the appropriate mathematical framework for constructing these landscapes. This allows the construction of minimally parameterized models consistent with cell behavior. We review existing examples where geometrical models have been used to fit experimental data on cell fate and describe how spatial interactions between cells can be understood geometrically. This article is protected by copyright. All rights reserved.
Keyphrases
  • cell fate
  • electronic health record
  • single cell
  • induced apoptosis
  • big data
  • stem cells
  • signaling pathway
  • machine learning
  • network analysis