JSP Special Issue on Statistical Theory of Biological Evolution

JSP Special Issue on Statistical Theory of Biological Evolution J Stat Phys (2018) 172:1–2 https://doi.org/10.1007/s10955-018-2057-2 JSP Special Issue on Statistical Theory of Biological Evolution 1 2 Kavita Jain · Luca Peliti Published online: 10 May 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 In an influential essay, Dobzhansky famously stated that “nothing in biology makes sense except in the light of evolution”. Indeed evolutionary processes shape diversity at all levels of biological organization, ranging from cellular to species and community level. In recent years, new methods and approaches have allowed to gain insight in evolutionary processes in real time via long-term evolution experiments or by high-resolution lineage tracking. Theoretical works using techniques borrowed from statistical physics and probability theory have helped greatly to understand the intricate process of evolution quantitatively. The objective of this special issue of Journal of Statistical Physics is to provide a view of some of the advances made in the field and of the current status of some outstanding and challenging problems. A biological population evolves under the action of basic processes, viz., selection, muta- tion, migration and random genetic drift (stochastic fluctuations arising due to sampling) and its dynamics are described by high-dimensional partial differential equations that are, in general, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Statistical Physics Springer Journals

JSP Special Issue on Statistical Theory of Biological Evolution

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Physics; Statistical Physics and Dynamical Systems; Theoretical, Mathematical and Computational Physics; Physical Chemistry; Quantum Physics
ISSN
0022-4715
eISSN
1572-9613
D.O.I.
10.1007/s10955-018-2057-2
Publisher site
See Article on Publisher Site

Abstract

J Stat Phys (2018) 172:1–2 https://doi.org/10.1007/s10955-018-2057-2 JSP Special Issue on Statistical Theory of Biological Evolution 1 2 Kavita Jain · Luca Peliti Published online: 10 May 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 In an influential essay, Dobzhansky famously stated that “nothing in biology makes sense except in the light of evolution”. Indeed evolutionary processes shape diversity at all levels of biological organization, ranging from cellular to species and community level. In recent years, new methods and approaches have allowed to gain insight in evolutionary processes in real time via long-term evolution experiments or by high-resolution lineage tracking. Theoretical works using techniques borrowed from statistical physics and probability theory have helped greatly to understand the intricate process of evolution quantitatively. The objective of this special issue of Journal of Statistical Physics is to provide a view of some of the advances made in the field and of the current status of some outstanding and challenging problems. A biological population evolves under the action of basic processes, viz., selection, muta- tion, migration and random genetic drift (stochastic fluctuations arising due to sampling) and its dynamics are described by high-dimensional partial differential equations that are, in general,

Journal

Journal of Statistical PhysicsSpringer Journals

Published: May 10, 2018

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