Burton Voorhees
SFI Seminar
Burton Voorhees, Athabasca University will speak on “Information Spread in Structured Populations.”
Tuesday April 2 • 12:15 p.m. • Collins Conference Room
Abstract: Given a finite, genetically homogeneous population, suppose that a single mutant in introduced.
What is the probability this mutant will become fixed in the population? In 1958 the Australian statistician Patrick Moran answered this question for birth-death processes in unstructured populations.
Whether and how the introduction of structure in the population alters the Moran result, however, has been extensively studied for only a few years.
This talk presents an adaptation of the Moran birth-death model of evolutionary processes on graphs. The model makes use of the full population state space, consisting of 2N binary valued vectors, and a Markov process on this space with transition matrix defined by the edge weight matrix of the given graph.
Simple graphs that suppress or enhance selection with respect to the Moran process are analyzed and new analytic results presented. One interesting result is that in some cases a graph may enhance selection relative to a complete graph for only limited values of fitness.
The model used, and related models, have a large variety of potential applications outside of population genetics, including models of: biological defenses against cancer; neural network information processing; the spread of innovations and rumors; tracing sources of computer viruses and epidemics, as well as more sinister possibilities.
Note: We are unable to accommodate members of the public for SFI’s limited lunch service; you’re welcome to bring your own.
SFI Host: Cris Moore
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The Santa Fe Institute is a nonprofit research center located in Santa Fe, New Mexico. Its scientists collaborate across disciplines to understand the complex systems that underlie critical questions for science and humanity. The Institute is supported by philanthropic individuals and foundations, forward-thinking partner companies, and government science agencies.
