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Stochasticity in cellular metabolism and growth: Approaches and consequences

  • FOM Institute for Atomic and Molecular Physics (AMOLF)
  • Delft University of Technology
  • PSL Research University

Résultats de recherche: Contribution à un journalArticle de révisionRevue par des pairs

16 Citations (Scopus)

Résumé

Advances in our ability to zoom in on single cells have revealed striking heterogeneity within isogenic populations. Attention has so far focussed predominantly on underlying stochastic variability in regulatory pathways and downstream differentiation events. In contrast, the role of stochasticity in metabolic processes and networks has long remained unaddressed. Here we review recent studies that have begun to overcome key technical challenges in addressing this issue. First findings have already demonstrated that metabolic networks are stochastic in nature, and highlight the plethora of cellular processes that are critically affected by it.

langue originaleAnglais
Pages (de - à)131-136
Nombre de pages6
journalCurrent Opinion in Systems Biology
Volume8
Les DOIs
étatPublié - 1 avr. 2018
Modification externeOui

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