arrow
Return

Predicting evolution

delete2017-02-21
delete199
PRE
AI
M
Michael Lässig *
V
Ville Mustonen *
A
Aleksandra M. Walczak *
DOI:10.1038/s41559-017-0077delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
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.
Keywords:
EMPIRICAL FITNESS LANDSCAPES
FACTOR-BINDING-SITES
ANTIBIOTIC-RESISTANCE
DRUG-RESISTANCE
BENEFICIAL MUTATIONS
POPULATION-GENETICS
CLONAL INTERFERENCE
ADAPTIVE EVOLUTION
GENOME EVOLUTION
T-CELLS
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Nature Ecology and Evolution cover
Nature Ecology and Evolution
IF:
14.5
Papers:
2.8K
Citations:
2.2W

Organization

U
University of Cologne
Scholars:
3.0W
Papers: 2.1W
Citations: 2.4W
W
wellcome trust sanger institute
Scholars:
6.9K
Papers: 4.3K
Citations: 17
U
Universite PSL
Scholars:
3.3W
Papers: 2.5W
Citations: 91
researcher View more organizations