Sci Am. Aug;(2) Antichaos and adaptation. Kauffman SA(1). Author information: (1)University of Pennsylvania, School of Medicine. Erratum in . English[edit]. Etymology[edit]. anti- + chaos, coined by Stuart Kauffman in Antichaos and Adaptation (published in Scientific American, August ). Antichaos and Adaptation Biological evolution may have been shaped by more than just natural selection. Computer models suggest that.

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We may have begun to understand evolution as the marriage of selection and self-organization. Packard of the University of Illinois at Champaign-Urbana may have been the first person to ask whether selection could drive parallel-processing Boolean networks to the edge of chaos. Differentiation, according to this model, would be a response to perturbations that carried a cell into the basin of attraction for another cell type.

Minimal perturbations in those systems cause avalanches of damage that can alter the behavior of most of the unfrozen elements. Another prediction refers to the stability of cell types. These properties are observed in organisms. For each combination, either an active or inactive result must be specified. The stability of attractors subjected to minimal perturbations can differ.

A structural perturbation is a permanent mutation in the connections or in the Boolean functions of a network. To study the behavior of thousands of elements when they are coupled together, I used a class of systems called random Boolean networks. Big attractors are stable to many perturbations, and small ones are generally unstable.

In contrast, if the level of bias is well below the critical value-as it is in chaotically active systems-then a web of oscillating elements spreads across the system, leaving only small islands of frozen elements. Minimal perturbations cause numerous small avalanches and a few large avalanches. One can calculate how many Boolean functions could conceivably apply to any binary element in a network. A critical feature of random Boolean networks is that they have a finite number of states.

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Networks on the boundary between order and chaos may have the flexibility to adapt rapidly and successfully through the accumulation of useful variations. Of these, the self-regulating network of a genome the complete set of genes in an organism offers a good example of how antichaos may govern development. The coordinated behavior of this system underlies cellular differentiation. To understand how self-organization can be a force in evolution, a brief overview of complex systems is necessary.

Typically only a few percent of the genes should show different activities. Both claims hold true for biological systems. Some can recover from any single perturbation, others from only a few, whereas still others are destabilized by any perturbation. Alternatively, the AND function declares that a variable will become active only if all its inputs are currently wdaptation. Usually each gene is directly regulated by few other genes of molecules-perhaps no more than All the network populations improved at playing the games faster than chance alone could accomplish.

In such poised systems, most mutations have small consequences because of the systems’ homeostatic nature. Understanding the logic and structure of the genomic regulatory system has therefore become a central task of molecular biology.

Antichaos and adaptation.

Kauffman Antichaos and Adaptation. In a Boolean network, each variable is regulated by others that serve as inputs. The parallels support the hypothesis that evolution has tuned adaptive gene regulatory systems to the ordered region and perhaps to near the boundary between order and chaos.

But a stable cell type persists in expressing restricted sets of genes. Interesting dynamic behaviors emerge at the edge of chaos. Highly ordered networks are too frozen to coordinate complex behavior.

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If the biases in an ordered network are lowered to a point near the critical value, it is possible to “melt” slightly the frozen components.

Antichaos and Adaptation

One phenomenon found in some cases has already caught the popular imagination: The complexity that a network can coordinate peaks at the liquid transition between solid and gaseous states.

After receiving an appropriate stimulus, a gene in a eukaryotic cell needs about one to 10 minutes to become active.

A minimal perturbation is a transient flipping of a binary element to its opposite state of activity. Chaos, fascinating as it is, is only part of the behavior of complex systems.

28cha: S. Kauffman Antichaos and Adaptation

Every complex system has what can be called local features: If we assume that the number of genes is proportional to the amount of DNA in a cell, then humans should have aboutgenes and cell types.

The discovery of antichaos in biology began more than 20 years ago with my efforts to understand mathematically how a fertilized egg differentiates into multitudes of cell types. Packard found such evolution occurring in a population of simple Boolean networks called cellular automata, which had been selected for their ability to perform a specific simple computation. Kauffman Scientific American, Augustpp Changes in activity should be restricted to small, isolated islands of genes.