Lahoz-Beltra Rafael, Navarro Jorge, Marijuán Pedro C
Department of Applied Mathematics (Biomathematics), Faculty of Biological Sciences, Complutense University of Madrid Madrid, Spain.
Instituto Aragonés de Ciencias de la Salud Zaragoza, Spain.
Front Microbiol. 2014 Mar 25;5:101. doi: 10.3389/fmicb.2014.00101. eCollection 2014.
The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.
与环境建立适应性关系的能力是活细胞的一个基本特征。细菌计算和细菌智能是沿着对周围环境条件作出反应的适应性行为所表现出的两个普遍特征。这两个特征已经产生了各种各样的理论和应用方法。由于细菌信号传导的不同系统和基因变化的不同方式已为人所知且得到了更深入的探索,细菌的整体适应可能性或许可以从新的角度进行研究。例如,沿着进化机制出现了分子“学习”的实例。更具体地说,从时间维度来看,细菌的学习和进化机制似乎是两种不同但相关的适应环境的机制;在体细胞时间里是前者,在进化时间里是后者。在本章中,将回顾这两种机制在原核分子计算方案以及解决现实世界问题方面的可能应用。