Sci Am. Aug;(2) Antichaos and adaptation. Kauffman SA(1). Author information: (1)University of Pennsylvania, School of Medicine. Erratum in . English. Etymology. 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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The more compressed the code, the less capacity it has to evolve. If such a change does not move a network outside its original basin of attraction, the network will eventually return to its original state cycle.
Antichaos and Adaptation
They have found that if the degree of bias exceeds a critical value, then “homogeneity clusters” of elements that have frozen values link with one another and percolate across the network. A system with elements and states, for example, would have only about 74 different patterns of behavior. Kauffman Scientific American, Augustpp For example, a hormone called ecdysone in the fruit fly Drosophila can unleash a cascade that changes the activity of about genes out of at least 5, That order, of course, is much the same as I have described for networks with low connectivity.
Like minimal perturbations, structural perturbations can cause damage, and networks may vary in their stability against them.
Since then, mathematicians, computer scientists and solid state physicists, among them my adpatation colleagues at the Santa Fe Institute in New Mexico, have made substantial progress. The network behaves chaotically.
Taken as models of genomic systems, systems poised between order and chaos come close to fitting many features of cellular differentiation during ontogeny-features common to organisms that have been diverging evolutionarily for more than million years.
Cell types differ because they have dissimilar patterns of genetic activity, not because they have different genes. The stability of an attractor is proportional to its basin size, which is the number of states on trajectories that drain into the attractor.
Antichaos and adaptation.
Highly ordered networks are too frozen to coordinate complex behavior. Selection has molded, but was not compelled to invent, the native coherence of ontogeny, or biological development.
Big attractors are stable to many perturbations, and small ones are generally unstable. By the most recent count, humans have about distinct cell types, so that prediction is also in the right range.
The frozen core creates interlinked walls of constancy that “percolate” or grow across the entire system. For example, in a genome the elements are genes. The mathematically idealized versions of biological systems I shall discuss are called autonomous random Boolean NK networks. Interesting dynamic behaviors emerge at the edge of chaos. That stable core of elements is identical in almost all the attractors.
Antichaos and adaptation. – Abstract – Europe PMC
The hypothesis is bold, perhaps even beautiful, but is it true? The efforts are still so new that there is not yet even a generally accepted, comprehensive definition of complexity. The expected size of avalanches in canalizing genomes with 5, elements or in those with low connectivity and a frozen core containing roughly 80 percent of the genes is about Even if each state transition took only one microsecond, it would take billions of times longer than the age of the universe for the network to traverse its attractor completely.
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. Yet certain properties of complex systems are becoming clear.
Antichaos and adaptation.
He has related network behavior to the phases adzptation matter: At that phase transition, both small and large unfrozen islands would exist. Consequently, in random networks with only two inputs per element, each attractor is antichxos to most minimal perturbations.
There is also a counterintuitive phenomenon that might be called antichaos: During the past two decades, there has been an explosion of interest in such systems throughout the natural and social sciences.
Some Boolean functions turn elements on more often than off or vice versa. Minimal perturbations in those systems cause avalanches of damage that can alter the behavior anticuaos most of the unfrozen elements. These islands are functionally isolated: One phenomenon found in some cases has already caught the popular imagination: Consequently, ontological development from a fertilized egg should proceed by successive branching pathways of differentiation.
An OR function for two inputs, for example, will turn an element on in response to three out of the four possible combinations of binary signals.
The activity of any one gene is directly regulated by fairly few other genes or gene products, and certain rules govern their interactions. But Darwin could not have suspected the existence of self-organization, a recently discovered, innate property of some complex systems.