Solé Ricard
ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr Aiguader 88, 08003 Barcelona, Spain Institut de Biologia Evolutiva, CSIC-UPF, Pg Maritim de la Barceloneta 37, 08003 Barcelona, Spain Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
Philos Trans R Soc Lond B Biol Sci. 2016 Aug 19;371(1701). doi: 10.1098/rstb.2015.0438.
The evolution of life in our biosphere has been marked by several major innovations. Such major complexity shifts include the origin of cells, genetic codes or multicellularity to the emergence of non-genetic information, language or even consciousness. Understanding the nature and conditions for their rise and success is a major challenge for evolutionary biology. Along with data analysis, phylogenetic studies and dedicated experimental work, theoretical and computational studies are an essential part of this exploration. With the rise of synthetic biology, evolutionary robotics, artificial life and advanced simulations, novel perspectives to these problems have led to a rather interesting scenario, where not only the major transitions can be studied or even reproduced, but even new ones might be potentially identified. In both cases, transitions can be understood in terms of phase transitions, as defined in physics. Such mapping (if correct) would help in defining a general framework to establish a theory of major transitions, both natural and artificial. Here, we review some advances made at the crossroads between statistical physics, artificial life, synthetic biology and evolutionary robotics.This article is part of the themed issue 'The major synthetic evolutionary transitions'.
我们生物圈中生命的演化以几项重大创新为标志。这种重大的复杂性转变包括细胞的起源、遗传密码或多细胞性,到非遗传信息、语言乃至意识的出现。理解这些转变产生及成功的本质和条件是进化生物学面临的一项重大挑战。除了数据分析、系统发育研究和专门的实验工作外,理论和计算研究也是这一探索的重要组成部分。随着合成生物学、进化机器人学、人工生命和先进模拟技术的兴起,针对这些问题的新视角引发了一个相当有趣的局面,即不仅可以研究甚至重现重大转变,而且甚至可能识别出新的转变。在这两种情况下,转变都可以根据物理学中定义的相变来理解。这种映射(如果正确)将有助于定义一个通用框架,以建立一个关于自然和人工重大转变的理论。在此,我们回顾在统计物理学、人工生命、合成生物学和进化机器人学交叉领域取得的一些进展。本文是主题为“重大合成进化转变”特刊的一部分。