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Review
. 2010 Dec;20(6):574-80.
doi: 10.1016/j.gde.2010.09.004. Epub 2010 Oct 9.

Approaching the molecular origins of collective dynamics in oscillating cell populations

Pankaj Mehta  1 , Thomas Gregor
Affiliations
Review

Approaching the molecular origins of collective dynamics in oscillating cell populations

Pankaj Mehta et al. Curr Opin Genet Dev. 2010 Dec.

Abstract

From flocking birds, to organ generation, to swarming bacterial colonies, biological systems often exhibit collective behaviors. Here, we review recent advances in our understanding of collective dynamics in cell populations. We argue that understanding population-level oscillations requires examining the system under consideration at three different levels of complexity: at the level of isolated cells, homogenous populations, and spatially structured populations. We discuss the experimental and theoretical challenges this poses and highlight how new experimental techniques, when combined with conceptual tools adapted from physics, may help us overcome these challenges.

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Figures

Figure 1
Figure 1. Collective behaviors in biology at different levels of complexity
Top: Collective behaviors in biology exist at the molecular (mitotic spindle formation [1]), the cellular (social amoebae aggregation [4]) and the organismal (schooling fish [8]) levels. This review focuses on systems at the cellular level. Cellular organism retain many of the interesting phenomena found in higher-order organisms such as information processing and collective decision making, with the added advantage that behavior can be directly linked to processes at the molecular level. Bottom: Cellular systems can be analyzed at three different levels of complexity, at the level of isolated cells, homogenous cell populations, and spatially-structured populations [77]. Understanding behavior requires systematic examination of these systems at all three levels of complexity. The main challenge faced when examining these systems is to link behavior at the single cell level to that of populations and vice versa.
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