TY - JOUR
T1 - Evolutionary Phase Transitions in Random Environments
AU - Skanata, Antun
AU - Kussell, Edo
N1 - Funding Information:
This research was supported by NIH Grant No.R01-GM-097356 and the James S. McDonnell Foundation Studying Complex Systems Research Grant No.220020275.
Publisher Copyright:
© 2016 American Physical Society.
PY - 2016/7/15
Y1 - 2016/7/15
N2 - We present analytical results for long-term growth rates of structured populations in randomly fluctuating environments, which we apply to predict how cellular response networks evolve. We show that networks which respond rapidly to a stimulus will evolve phenotypic memory exclusively under random (i.e., nonperiodic) environments. We identify the evolutionary phase diagram for simple response networks, which we show can exhibit both continuous and discontinuous transitions. Our approach enables exact analysis of diverse evolutionary systems, from viral epidemics to emergence of drug resistance.
AB - We present analytical results for long-term growth rates of structured populations in randomly fluctuating environments, which we apply to predict how cellular response networks evolve. We show that networks which respond rapidly to a stimulus will evolve phenotypic memory exclusively under random (i.e., nonperiodic) environments. We identify the evolutionary phase diagram for simple response networks, which we show can exhibit both continuous and discontinuous transitions. Our approach enables exact analysis of diverse evolutionary systems, from viral epidemics to emergence of drug resistance.
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U2 - 10.1103/PhysRevLett.117.038104
DO - 10.1103/PhysRevLett.117.038104
M3 - Article
C2 - 27472146
AN - SCOPUS:84978670332
SN - 0031-9007
VL - 117
JO - Physical Review Letters
JF - Physical Review Letters
IS - 3
M1 - 038104
ER -