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Quantitative Biology

, Volume 1, Issue 2, pp 131–139 | Cite as

Predictive power of cell-to-cell variability

  • Bochong Li
  • Lingchong YouEmail author
Review

Abstract

Much of our current knowledge of biology has been constructed based on population-average measurements. However, advances in single-cell analysis have demonstrated the omnipresent nature of cell-to-cell variability in any population. On one hand, tremendous efforts have been made to examine how such variability arises, how it is regulated by cellular networks, and how it can affect cell-fate decisions by single cells. On the other hand, recent studies suggest that the variability may carry valuable information that can facilitate the elucidation of underlying regulatory networks or the classification of cell states. To this end, a major challenge is determining what aspects of variability bear significant biological meaning. Addressing this challenge requires the development of new computational tools, in conjunction with appropriately chosen experimental platforms, to more effectively describe and interpret data on cell-cell variability. Here, we discuss examples of when population heterogeneity plays critical roles in determining biologically and clinically significant phenotypes, how it serves as a rich information source of regulatory mechanisms, and how we can extract such information to gain a deeper understanding of biological systems.

Keywords

Cellular Network Intrinsic Noise Phenotypic Heterogeneity Chemical Master Equation Probabilistic Boolean Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Higher Education Press and Springer-Verlag GmbH 2013

Authors and Affiliations

  1. 1.Department of Biomedical EngineeringDuke UniversityDurhamUSA
  2. 2.Center for Systems BiologyDuke UniversityDurhamUSA
  3. 3.Institute for Genome Sciences and PolicyDuke UniversityDurhamUSA

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