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Nat Rev Microbiol. 2016 Jul;14(7):461-71. doi: 10.1038/nrmicro.2016.62. Epub 2016 Jun 6.

Advancing microbial sciences by individual-based modelling.

Author information

1
Department of Civil and Environmental Engineering, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, USA.
2
Centre for Computational Biology &Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK.
3
Plymouth Marine Laboratory, Prospect Place, Plymouth, PL1 3DH, UK.
4
Laboratory of Microbiology, Wageningen University, 6708 WE Wageningen, The Netherlands.

Abstract

Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage-CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (╬╝IBE).

PMID:
27265769
DOI:
10.1038/nrmicro.2016.62
[Indexed for MEDLINE]

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