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Nat Ecol Evol. 2017 Feb 21;1(3):77. doi: 10.1038/s41559-017-0077.

Predicting evolution.

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Institute of Theoretical Physics, University of Cologne, 50937 Cologne, Germany.
Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK.
Laboratoire de Physique Théorique CNRS, Ecole Normale Supérieure, 75005 Paris, France.


The face of evolutionary biology is changing: from reconstructing and analysing the past to predicting future evolutionary processes. Recent developments include prediction of reproducible patterns in parallel evolution experiments, forecasting the future of individual populations using data from their past, and controlled manipulation of evolutionary dynamics. Here we undertake a synthesis of central concepts for evolutionary predictions, based on examples of microbial and viral systems, cancer cell populations, and immune receptor repertoires. These systems have strikingly similar evolutionary dynamics driven by the competition of clades within a population. These dynamics are the basis for models that predict the evolution of clade frequencies, as well as broad genetic and phenotypic changes. Moreover, there are strong links between prediction and control, which are important for interventions such as vaccine or therapy design. All of these are key elements of what may become a predictive theory of evolution.


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