Neutral fitness landscapes in signalling networks.

Netcrawling - Optimal Evolutionary Search with Neutral Networks

Several studies have demonstrated that in the presence of a high degree of selective neutrality, in particular on fitness landscapes featuring neutral networks, evolution is qualitatively different from that on the more common model of rugged/correlated fitness landscapes often (implicitly) assumed by GA researchers. We characterise evolutionary dynamics on fitness landscapes with neutral netwo...

TANGLED WEBS Evolutionary Dynamics on Fitness Landscapes with Neutrality

3 After a while your adversaries and competitors will give up trying to think of alternative hypotheses, or else will grow old and die, and then your hypothesis will become accepted. Sounds crazy, we know, but that's how science works!-Numerical Recipes in C Abstract The bulk of research on the dynamics of populations of genotypes evolving on fitness landscapes has concentrated on the rôle of c...

Ruggedness and Neutrality - The NKp family of Fitness Landscapes

It has come to be almost an article of faith amongst population biologists and GA researchers alike that the principal feature of a fitness landscape as regards evolutionary dynamics is “ruggedness”, particularly as measured by the auto-correlation function. In this paper we demonstrate that auto-correlation alone may be inadequate as a mediator of evolutionary dynamics, specifically in the pre...

Evolutionary search on fitness landscapes with neutral networks

Fitness Landscapes Arising from the Sequence-Structure Maps of Biopolymers

Fitness landscapes are an important concept in molecular evolution since evolutionary adaptation as well as in vitro selection of biomolecules can be viewed as a hill-climbing-like process. Global features of landscapes can be described by statistical measures such as correlation functions or the fraction of neutral (equally fit) neighbors. Simple spin-glass-like landscape models borrowed from ...

Finding Needles in Haystacks Is Not Hard with Neutrality

We propose building neutral networks in needle-in-haystack fitness landscapes to assist an evolutionary algorithm to perform search. The experimental results on four different problems show that this approach improves the search success rates in most cases. In situations where neutral networks do not give performance improvement, no impairment occurs either. We also tested a hypothesis proposed...